-
1
-
-
0029237466
-
Novelty detection for the identification of masses in mammograms
-
L. Tarassenko, P. Hayton, N. Cerneaz, M. Brady, Novelty detection for the identification of masses in mammograms, in: Proceedings of the 4th International Conference on Artificial Neural Networks, IET, 1995, pp. 442-447.
-
(1995)
Proceedings of the 4th International Conference on Artificial Neural Networks, IET
, pp. 442-447
-
-
Tarassenko, L.1
Hayton, P.2
Cerneaz, N.3
Brady, M.4
-
2
-
-
38149031678
-
Known unknowns novelty detection in condition monitoring
-
J. Quinn, and C. Williams Known unknowns novelty detection in condition monitoring Pattern Recognit. Image Anal. 4477 2007 1 6
-
(2007)
Pattern Recognit. Image Anal.
, vol.4477
, pp. 1-6
-
-
Quinn, J.1
Williams, C.2
-
3
-
-
83155184726
-
Identification of patient deterioration in vital-sign data using one-class support vector machines
-
L. Clifton, D. Clifton, P. Watkinson, L. Tarassenko, Identification of patient deterioration in vital-sign data using one-class support vector machines, in: Proceedings of the Federated Conference on Computer Science and Information Systems (FedCSIS), IEEE, 2011, pp. 125-131.
-
(2011)
Proceedings of the Federated Conference on Computer Science and Information Systems (FedCSIS), IEEE
, pp. 125-131
-
-
Clifton, L.1
Clifton, D.2
Watkinson, P.3
Tarassenko, L.4
-
5
-
-
77949485006
-
Novelty detection in a changing environment a negative selection approach
-
C. Surace, and K. Worden Novelty detection in a changing environment a negative selection approach Mech. Syst. Signal Process. 24 4 2010 1114 1128
-
(2010)
Mech. Syst. Signal Process.
, vol.24
, Issue.4
, pp. 1114-1128
-
-
Surace, C.1
Worden, K.2
-
6
-
-
34250315640
-
An overview of anomaly detection techniques: Existing solutions and latest technological trends
-
DOI 10.1016/j.comnet.2007.02.001, PII S138912860700062X
-
A. Patcha, and J. Park An overview of anomaly detection techniques existing solutions and latest technological trends Comput. Netw. 51 12 2007 3448 3470 (Pubitemid 46921030)
-
(2007)
Computer Networks
, vol.51
, Issue.12
, pp. 3448-3470
-
-
Patcha, A.1
Park, J.-M.2
-
8
-
-
0036080023
-
Real-time object classification and novelty detection for collaborative video surveillance
-
C. Diehl, J. Hampshire, Real-time object classification and novelty detection for collaborative video surveillance, in: Proceedings of the International Joint Conference on Neural Networks, IJCNN'02, 2002, vol. 3, pp. 2620-2625. (Pubitemid 34648045)
-
(2002)
Proceedings of the International Joint Conference on Neural Networks
, vol.3
, pp. 2620-2625
-
-
Diehl, C.P.1
Hampshire II, J.B.2
-
11
-
-
79959563317
-
Anytime online novelty and change detection for mobile robots
-
B. Sofman, B. Neuman, A. Stentz, and J. Bagnell Anytime online novelty and change detection for mobile robots J. Field Robot. 28 4 2011 589 618
-
(2011)
J. Field Robot.
, vol.28
, Issue.4
, pp. 589-618
-
-
Sofman, B.1
Neuman, B.2
Stentz, A.3
Bagnell, J.4
-
12
-
-
77955082590
-
Outlier detection techniques for wireless sensor networks a survey
-
Y. Zhang, N. Meratnia, and P. Havinga Outlier detection techniques for wireless sensor networks a survey IEEE Commun. Surv. Tutor. 12 2 2010 159 170
-
(2010)
IEEE Commun. Surv. Tutor.
, vol.12
, Issue.2
, pp. 159-170
-
-
Zhang, Y.1
Meratnia, N.2
Havinga, P.3
-
13
-
-
70349253476
-
Distributed top-k outlier detection from astronomy catalogs using the DEMAC system
-
H. Dutta, C. Giannella, K. Borne, H. Kargupta, Distributed top-k outlier detection from astronomy catalogs using the DEMAC system, in: Proceedings of the 7th SIAM International Conference on Data Mining, IEEE, 2007.
-
(2007)
Proceedings of the 7th SIAM International Conference on Data Mining, IEEE
-
-
Dutta, H.1
Giannella, C.2
Borne, K.3
Kargupta, H.4
-
15
-
-
12244300524
-
A probabilistic framework for semi-supervised clustering
-
KDD-2004 - Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
-
S. Basu, M. Bilenko, R. Mooney, A probabilistic framework for semi-supervised clustering, in: Proceedings of the 10th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), ACM, 2004, pp. 59-68. (Pubitemid 40114916)
-
(2004)
KDD-2004 - Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
, pp. 59-68
-
-
Basu, S.1
Bilenko, M.2
Mooney, R.J.3
-
18
-
-
0010142578
-
One-class classifier networks for target recognition applications
-
M. Moya, M. Koch, L. Hostetler, One-class classifier networks for target recognition applications, in: Proceedings of the World Congress on Neural Networks, International Neural Network Society, 1993, pp. 797-801.
-
(1993)
Proceedings of the World Congress on Neural Networks, International Neural Network Society
, pp. 797-801
-
-
Moya, M.1
Koch, M.2
Hostetler, L.3
-
19
-
-
68549133155
-
Learning from imbalanced data
-
H. He, and E. Garcia Learning from imbalanced data IEEE Trans. Knowl. Data Eng. 21 9 2009 1263 1284
-
(2009)
IEEE Trans. Knowl. Data Eng.
, vol.21
, Issue.9
, pp. 1263-1284
-
-
He, H.1
Garcia, E.2
-
20
-
-
33750717188
-
The novelty detection approach for different degrees of class imbalance
-
Neural Information Processing - 13th International Conference, ICONIP 2006, Proceedings
-
H.-J. Lee, and S. Cho The novelty detection approach for different degrees of class imbalance I. King, J. Wang, L.-W. Chan, D. Wang, Neural Information Processing, Lecture Notes in Computer Science vol. 4233 2006 Springer Berlin/Heidelberg 21 30 (Pubitemid 44699706)
-
(2006)
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
, vol.4233 LNCS - II
, pp. 21-30
-
-
Lee, H.-J.1
Cho, S.2
-
21
-
-
0028480283
-
Novelty detection and neural network validation
-
IET
-
C. Bishop, Novelty detection and neural network validation, in: Proceedings of the IEEE Conference on Vision, Image and Signal Processing, vol. 141, IET, 1994, pp. 217-222.
-
(1994)
Proceedings of the IEEE Conference on Vision, Image and Signal Processing
, vol.141
, pp. 217-222
-
-
Bishop, C.1
-
22
-
-
0031169206
-
Outliers in statistical pattern recognition and an application to automatic chromosome classification
-
PII S0167865597000494
-
G. Ritter, and M. Gallegos Outliers in statistical pattern recognition and an application to automatic chromosome classification Pattern Recognit. Lett. 18 6 1997 525 539 (Pubitemid 127424200)
-
(1997)
Pattern Recognition Letters
, vol.18
, Issue.6
, pp. 525-539
-
-
Ritter, G.1
Gallegos, M.T.2
-
26
-
-
0142063407
-
Novelty detection: A review - Part 1 statistical approaches
-
M. Markou, and S. Singh Novelty detection: a review - part 1 statistical approaches Signal Process. 83 12 2003 2481 2497
-
(2003)
Signal Process.
, vol.83
, Issue.12
, pp. 2481-2497
-
-
Markou, M.1
Singh, S.2
-
27
-
-
0142126712
-
Novelty detection a review - Part 2: Neural network based approaches
-
M. Markou, and S. Singh Novelty detection a review - part 2: neural network based approaches Signal Process. 83 12 2003 2499 2521
-
(2003)
Signal Process.
, vol.83
, Issue.12
, pp. 2499-2521
-
-
Markou, M.1
Singh, S.2
-
28
-
-
8844281752
-
Novelty detection in learning systems
-
S. Marsland Novelty detection in learning systems Neural Comput. Surv. 3 2003 157 195
-
(2003)
Neural Comput. Surv.
, vol.3
, pp. 157-195
-
-
Marsland, S.1
-
29
-
-
7544223741
-
A survey of outlier detection methodologies
-
V. Hodge, and J. Austin A survey of outlier detection methodologies Artif. Intell. Rev. 22 2 2004 85 126
-
(2004)
Artif. Intell. Rev.
, vol.22
, Issue.2
, pp. 85-126
-
-
Hodge, V.1
Austin, J.2
-
30
-
-
47949100550
-
A comprehensive survey of numeric and symbolic outlier mining techniques
-
M. Agyemang, K. Barker, and R. Alhajj A comprehensive survey of numeric and symbolic outlier mining techniques Intell. Data Anal. 10 6 2006 521 538
-
(2006)
Intell. Data Anal.
, vol.10
, Issue.6
, pp. 521-538
-
-
Agyemang, M.1
Barker, K.2
Alhajj, R.3
-
31
-
-
42749099167
-
A comparative study for outlier detection techniques in data mining
-
Z. Bakar, R. Mohemad, A. Ahmad, M. Deris, A comparative study for outlier detection techniques in data mining, in: Proceedings of the IEEE Conference on Cybernetics and Intelligent Systems, IEEE, 2006, pp. 1-6.
-
(2006)
Proceedings of the IEEE Conference on Cybernetics and Intelligent Systems, IEEE
, pp. 1-6
-
-
Bakar, Z.1
Mohemad, R.2
Ahmad, A.3
Deris, M.4
-
32
-
-
78650080782
-
A survey of recent trends in one class classification
-
L. Coyle, J. Freyne, Springer Berlin/Heidelberg
-
S. Khan, and M. Madden A survey of recent trends in one class classification L. Coyle, J. Freyne, Artificial Intelligence and Cognitive Science, Lecture Notes in Computer Science vol. 6206 2010 Springer Berlin/Heidelberg 188 197
-
(2010)
Artificial Intelligence and Cognitive Science, Lecture Notes in Computer Science
, vol.6206 VOL.
, pp. 188-197
-
-
Khan, S.1
Madden, M.2
-
35
-
-
65649091327
-
Analysis of time series novelty detection strategies for synthetic and real data
-
A. Modenesi, and A. Braga Analysis of time series novelty detection strategies for synthetic and real data Neural Process. Lett. 30 1 2009 1 17
-
(2009)
Neural Process. Lett.
, vol.30
, Issue.1
, pp. 1-17
-
-
Modenesi, A.1
Braga, A.2
-
36
-
-
60949113326
-
-
University of Minnesota
-
V. Chandola, A. Banerjee, V. Kumar, Outlier Detection: A Survey, Technical Report 07-017, University of Minnesota, 2007.
-
(2007)
Outlier Detection: A Survey, Technical Report 07-017
-
-
Chandola, V.1
Banerjee, A.2
Kumar, V.3
-
37
-
-
84893259155
-
Domain anomaly detection in machine perception: A system architecture and taxonomy
-
J. Kittler, W. Christmas, T. de Campos, D. Windridge, F. Yan, J. Illingworth, M. Osman, Domain anomaly detection in machine perception: a system architecture and taxonomy, IEEE Trans. Pattern Anal. Mach. Intell. 99 (2013) 1.
-
(2013)
IEEE Trans. Pattern Anal. Mach. Intell.
, vol.99
, pp. 1
-
-
Kittler, J.1
Christmas, W.2
De Campos, T.3
Windridge, D.4
Yan, F.5
Illingworth, J.6
Osman, M.7
-
38
-
-
84855359945
-
Anomaly, novelty, one-class classification a comprehensive introduction
-
A.M. Bartkowiak Anomaly, novelty, one-class classification a comprehensive introduction Int. J. Comput. Inf. Syst. Ind. Manage. Appl. 3 2011 61 71
-
(2011)
Int. J. Comput. Inf. Syst. Ind. Manage. Appl.
, vol.3
, pp. 61-71
-
-
Bartkowiak, A.M.1
-
39
-
-
84863951242
-
Novelty detection for cumulative learning
-
Y. Gatsoulis, E. Kerr, J. Condell, N. Siddique, T. McGinnity, Novelty detection for cumulative learning, in: Proceedings of the Conference on Towards Autonomous Robotic Systems, 2010, pp. 62-67.
-
(2010)
Proceedings of the Conference on Towards Autonomous Robotic Systems
, pp. 62-67
-
-
Gatsoulis, Y.1
Kerr, E.2
Condell, J.3
Siddique, N.4
McGinnity, T.5
-
40
-
-
84893280827
-
Brief overview of novelty detection methods for robotic cumulative learning
-
E. Kerr, Y. Gatsoulis, N.H. Siddique, J.V. Condell, T.M. McGinnity, Brief overview of novelty detection methods for robotic cumulative learning, in: Proceedings of the 21st National Conference on Artificial Intelligence and Cognitive Science, 2010, pp. 171-180.
-
(2010)
Proceedings of the 21st National Conference on Artificial Intelligence and Cognitive Science
, pp. 171-180
-
-
Kerr, E.1
Gatsoulis, Y.2
Siddique, N.H.3
Condell, J.V.4
McGinnity, T.M.5
-
42
-
-
79953319913
-
Data mining based network intrusion detection system a survey
-
R. Helali Data mining based network intrusion detection system a survey Novel Algoritm. Tech. Telecommun. Netw. 2010 501 505
-
(2010)
Novel Algoritm. Tech. Telecommun. Netw.
, pp. 501-505
-
-
Helali, R.1
-
43
-
-
84946031884
-
Procedures for detecting outlying observations in samples
-
F.E. Grubbs Procedures for detecting outlying observations in samples Technometrics 11 1 1969 1 21
-
(1969)
Technometrics
, vol.11
, Issue.1
, pp. 1-21
-
-
Grubbs, F.E.1
-
45
-
-
28044457628
-
Detection of outliers in reference distributions: Performance of horn's algorithm
-
DOI 10.1373/clinchem.2005.058339
-
H. Solberg, and A. Lahti Detection of outliers in reference distributions performance of Horn's algorithm Clin. Chem. 51 12 2005 2326 2332 (Pubitemid 41692577)
-
(2005)
Clinical Chemistry
, vol.51
, Issue.12
, pp. 2326-2332
-
-
Solberg, H.E.1
Lahti, A.2
-
46
-
-
0014710323
-
On optimum recognition error and reject tradeoff
-
C. Chow On optimum recognition error and reject tradeoff IEEE Trans. Inf. Theory 16 1 1970 41 46
-
(1970)
IEEE Trans. Inf. Theory
, vol.16
, Issue.1
, pp. 41-46
-
-
Chow, C.1
-
47
-
-
84893268965
-
-
John Wiley & Sons, Inc.
-
D.W. Scott Frontmatter 2008 John Wiley & Sons, Inc.
-
(2008)
Frontmatter
-
-
Scott, D.W.1
-
48
-
-
46749089010
-
Real time novelty detection modeling for machine health prognostics
-
D. Filev, F. Tseng, Real time novelty detection modeling for machine health prognostics, in: Proceedings of the Annual Meeting of the North American Fuzzy Information Processing Society (NAFIPS), IEEE, 2006, pp. 529-534.
-
(2006)
Proceedings of the Annual Meeting of the North American Fuzzy Information Processing Society (NAFIPS), IEEE
, pp. 529-534
-
-
Filev, D.1
Tseng, F.2
-
49
-
-
34250702688
-
Novelty detection based machine health prognostics
-
DOI 10.1109/ISEFS.2006.251161, 4016725, Proceedings of the 2006 International Symposium on Evolving Fuzzy Systems, EFS'06
-
D. Filev, F. Tseng, Novelty detection based machine health prognostics, in: International Symposium on Evolving Fuzzy Systems, 2006, pp. 193-199. (Pubitemid 46948109)
-
(2006)
Proceedings of the 2006 International Symposium on Evolving Fuzzy Systems, EFS'06
, pp. 193-199
-
-
Filev, D.P.1
Tseng, F.2
-
50
-
-
33644630695
-
Novelty detection based on spectral similarity of songs
-
A. Flexer, E. Pampalk, G. Widmer, Novelty detection based on spectral similarity of songs, in: Proceedings of 6th International Conference on Music Information Retrieval, 2005, pp. 260-263.
-
(2005)
Proceedings of 6th International Conference on Music Information Retrieval
, pp. 260-263
-
-
Flexer, A.1
Pampalk, E.2
Widmer, G.3
-
51
-
-
34047236024
-
Gaussian mixture pdf in one-class classification: Computing and utilizing confidence values
-
DOI 10.1109/ICPR.2006.595, 1699271, Proceedings - 18th International Conference on Pattern Recognition, ICPR 2006
-
J. Ilonen, P. Paalanen, J. Kamarainen, H. Kalviainen, Gaussian mixture pdf in one-class classification: computing and utilizing confidence values, in: Proceedings of the 18th International Conference on Pattern Recognition (ICPR), vol. 2, IEEE, 2006, pp. 577-580. (Pubitemid 46532265)
-
(2006)
Proceedings - International Conference on Pattern Recognition
, vol.2
, pp. 577-580
-
-
Ilonen, J.1
Paalanen, P.2
Kamarainen, J.-K.3
Kalviainen, H.4
-
53
-
-
33646093001
-
Feature representation and discrimination based on Gaussian mixture model probability densities - Practices and algorithms
-
P. Paalanen, J. Kamarainen, J. Ilonen, and H. Kälviäinen Feature representation and discrimination based on Gaussian mixture model probability densities - practices and algorithms Pattern Recognit. 39 7 2006 1346 1358
-
(2006)
Pattern Recognit.
, vol.39
, Issue.7
, pp. 1346-1358
-
-
Paalanen, P.1
Kamarainen, J.2
Ilonen, J.3
Kälviäinen, H.4
-
54
-
-
17644399346
-
Unsupervised condition change detection in large diesel engines
-
N. Pontoppidan, J. Larsen, Unsupervised condition change detection in large diesel engines, in: Proceedings of the IEEE 13th Workshop on Neural Networks for Signal Processing, NNSP'03, IEEE, 2003, pp. 565-574.
-
(2003)
Proceedings of the IEEE 13th Workshop on Neural Networks for Signal Processing, NNSP'03, IEEE
, pp. 565-574
-
-
Pontoppidan, N.1
Larsen, J.2
-
55
-
-
33947697162
-
Conditional anomaly detection
-
X. Song, M. Wu, C. Jermaine, and S. Ranka Conditional anomaly detection IEEE Trans. Knowl. Data Eng. 19 5 2007 631 645
-
(2007)
IEEE Trans. Knowl. Data Eng.
, vol.19
, Issue.5
, pp. 631-645
-
-
Song, X.1
Wu, M.2
Jermaine, C.3
Ranka, S.4
-
56
-
-
18144377114
-
Novelty detection for practical pattern recognition in condition monitoring of multivariate processes: A case study
-
DOI 10.1007/s00170-004-2174-8
-
F. Zorriassatine, A. Al-Habaibeh, R. Parkin, M. Jackson, and J. Coy Novelty detection for practical pattern recognition in condition monitoring of multivariate processes a case study Int. J. Adv. Manuf. Technol. 25 9 2005 954 963 (Pubitemid 40609441)
-
(2005)
International Journal of Advanced Manufacturing Technology
, vol.25
, Issue.9-10
, pp. 954-963
-
-
Zorriassatine, F.1
Al-Habaibeh, A.2
Parkin, R.M.3
Jackson, M.R.4
Coy, J.5
-
58
-
-
72349086213
-
A comparison of approaches to multivariate extreme value theory for novelty detection
-
D. Clifton, S. Hugueny, L. Tarassenko, A comparison of approaches to multivariate extreme value theory for novelty detection, in: Proceedings of the IEEE/SP 15th Workshop on Statistical Signal Processing, IEEE, 2009, pp. 13-16.
-
(2009)
Proceedings of the IEEE/SP 15th Workshop on Statistical Signal Processing, IEEE
, pp. 13-16
-
-
Clifton, D.1
Hugueny, S.2
Tarassenko, L.3
-
59
-
-
81855226144
-
Novelty detection with multivariate extreme value statistics
-
D. Clifton, S. Hugueny, and L. Tarassenko Novelty detection with multivariate extreme value statistics J. Signal Process. Syst. 65 3 2011 371 389
-
(2011)
J. Signal Process. Syst.
, vol.65
, Issue.3
, pp. 371-389
-
-
Clifton, D.1
Hugueny, S.2
Tarassenko, L.3
-
60
-
-
82455210516
-
Pinning the tail on the distribution: A multivariate extension to the generalised Pareto distribution
-
D. Clifton, S. Hugueny, L. Tarassenko, Pinning the tail on the distribution: a multivariate extension to the generalised Pareto distribution, in: IEEE International Workshop on Machine Learning for Signal Processing (MLSP), 2011, pp. 1-6.
-
(2011)
IEEE International Workshop on Machine Learning for Signal Processing (MLSP)
, pp. 1-6
-
-
Clifton, D.1
Hugueny, S.2
Tarassenko, L.3
-
61
-
-
84873802598
-
An extreme function theory for novelty detection
-
D. Clifton, L. Clifton, S. Hugueny, D. Wong, and L. Tarassenko An extreme function theory for novelty detection IEEE J. Sel. Top. Signal Process. 7 1 2013 28 37
-
(2013)
IEEE J. Sel. Top. Signal Process.
, vol.7
, Issue.1
, pp. 28-37
-
-
Clifton, D.1
Clifton, L.2
Hugueny, S.3
Wong, D.4
Tarassenko, L.5
-
63
-
-
77950923335
-
Novelty detection with multivariate extreme value theory, part II: An analytical approach to unimodal estimation
-
S. Hugueny, D. Clifton, L. Tarassenko, Novelty detection with multivariate extreme value theory, part II: an analytical approach to unimodal estimation, in: Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, IEEE, 2009, pp. 1-6.
-
(2009)
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, IEEE
, pp. 1-6
-
-
Hugueny, S.1
Clifton, D.2
Tarassenko, L.3
-
64
-
-
0033359542
-
Novelty detection using extreme value statistics
-
DOI 10.1049/ip-vis:19990428
-
S. Roberts, Novelty detection using extreme value statistics, in: Proceedings of the IEEE Conference on Vision, Image and Signal Processing 146 (3) (1999) 124-129. (Pubitemid 30500232)
-
(1999)
IEE Proceedings: Vision, Image and Signal Processing
, vol.146
, Issue.3
, pp. 124-129
-
-
Roberts, S.J.1
-
65
-
-
0034313895
-
Extreme value statistics for novelty detection in biomedical data processing
-
DOI 10.1049/ip-smt:20000841
-
S. Roberts, Extreme value statistics for novelty detection in biomedical data processing, in: Proceedings of the IEEE Conference on Science, Measurement and Technology, vol. 147, IET, 2000, pp. 363-367. (Pubitemid 32134375)
-
(2000)
IEE Proceedings: Science, Measurement and Technology
, vol.147
, Issue.6
, pp. 363-367
-
-
Roberts, S.J.1
-
66
-
-
20144366598
-
Structural damage classification using extreme value statistics
-
DOI 10.1115/1.1849240
-
H. Sohn, D.W. Allen, K. Worden, and C.R. Farrar Structural damage classification using extreme value statistics J. Dyn. Syst. Meas. Control 127 1 2005 125 132 (Pubitemid 40773751)
-
(2005)
Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME
, vol.127
, Issue.1
, pp. 125-132
-
-
Sohn, H.1
Allen, D.W.2
Worden, K.3
Farrar, C.R.4
-
67
-
-
84905703368
-
Aircraft engine health monitoring using density modelling and extreme value statistics
-
S. Sundaram, D. Clifton, I. Strachan, L. Tarassenko, S. King, Aircraft engine health monitoring using density modelling and extreme value statistics, in: Proceedings of the 6th International Conference on Condition Monitoring and Machine Failure Prevention Technologies, 2009.
-
(2009)
Proceedings of the 6th International Conference on Condition Monitoring and Machine Failure Prevention Technologies
-
-
Sundaram, S.1
Clifton, D.2
Strachan, I.3
Tarassenko, L.4
King, S.5
-
68
-
-
79956319997
-
Markov models for identification of significant episodes
-
R. Gwadera, M. Atallah, W. Szpankowski, Markov models for identification of significant episodes, in: Proceedings of 5th SIAM International Conference on Data Mining, 2005, pp. 404-414.
-
(2005)
Proceedings of 5th SIAM International Conference on Data Mining
, pp. 404-414
-
-
Gwadera, R.1
Atallah, M.2
Szpankowski, W.3
-
70
-
-
33749540435
-
Adaptive event detection with time - Varying poisson processes
-
KDD 2006: Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
-
A. Ihler, J. Hutchins, P. Smyth, Adaptive event detection with time-varying poisson processes, in: Proceedings of the 12th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), ACM, 2006, pp. 207-216. (Pubitemid 44535517)
-
(2006)
Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
, vol.2006
, pp. 207-216
-
-
Ihler, A.1
Hutchins, J.2
Smyth, P.3
-
71
-
-
34247492538
-
Outlier detection in wireless sensor networks using Bayesian belief networks
-
D. Janakiram, V. Adi Mallikarjuna Reddy, A. Phani Kumar, Outlier detection in wireless sensor networks using Bayesian belief networks, in: Proceedings of the 1st International Conference on Communication System Software and Middleware (Comsware), IEEE, 2006, pp. 1-6.
-
(2006)
Proceedings of the 1st International Conference on Communication System Software and Middleware (Comsware), IEEE
, pp. 1-6
-
-
Janakiram, D.1
Adi Mallikarjuna Reddy, V.2
Phani Kumar, A.3
-
73
-
-
0036655291
-
Linear and non-linear methods for automatic seizure detection in scalp electro-encephalogram recordings
-
P. McSharry, T. He, L. Smith, and L. Tarassenko Linear and non-linear methods for automatic seizure detection in scalp electro-encephalogram recordings Med. Biol. Eng. Comput. 40 4 2002 447 461 (Pubitemid 34982537)
-
(2002)
Medical and Biological Engineering and Computing
, vol.40
, Issue.4
, pp. 447-461
-
-
McSharry, P.E.1
He, T.2
Smith, L.A.3
Tarassenko, L.4
-
75
-
-
79960670476
-
Probabilistic novelty detection for acoustic surveillance under real-world conditions
-
S. Ntalampiras, I. Potamitis, and N. Fakotakis Probabilistic novelty detection for acoustic surveillance under real-world conditions IEEE Trans. Multimed. 13 4 2011 713 719
-
(2011)
IEEE Trans. Multimed.
, vol.13
, Issue.4
, pp. 713-719
-
-
Ntalampiras, S.1
Potamitis, I.2
Fakotakis, N.3
-
76
-
-
80054796335
-
Novelty detection using graphical models for semantic room classification
-
A. Pinto, A. Pronobis, and L. Reis Novelty detection using graphical models for semantic room classification Prog. Artif. Intell. 7026 2011 326 339
-
(2011)
Prog. Artif. Intell.
, vol.7026
, pp. 326-339
-
-
Pinto, A.1
Pronobis, A.2
Reis, L.3
-
77
-
-
0037142572
-
Anomaly intrusion detection method based on HMM
-
DOI 10.1049/el:20020467
-
Y. Qiao, X. Xin, Y. Bin, and S. Ge Anomaly intrusion detection method based on HMM Electron. Lett. 38 13 2002 663 664 (Pubitemid 34725625)
-
(2002)
Electronics Letters
, vol.38
, Issue.13
, pp. 663-664
-
-
Qiao, Y.1
Xin, X.W.2
Bin, Y.3
Ge, S.4
-
78
-
-
67650995767
-
Factorial switching linear dynamical systems applied to physiological condition monitoring
-
J. Quinn, C. Williams, and N. McIntosh Factorial switching linear dynamical systems applied to physiological condition monitoring IEEE Trans. Pattern Anal. Mach. Intell. 31 9 2009 1537 1551
-
(2009)
IEEE Trans. Pattern Anal. Mach. Intell.
, vol.31
, Issue.9
, pp. 1537-1551
-
-
Quinn, J.1
Williams, C.2
McIntosh, N.3
-
79
-
-
2442505788
-
Towards multisensor data fusion for dos detection
-
ACM, New York, NY, USA
-
C. Siaterlis, B. Maglaris, Towards multisensor data fusion for dos detection, in: Proceedings of the ACM Symposium on Applied Computing, SAC '04, ACM, New York, NY, USA, 2004, pp. 439-446.
-
(2004)
Proceedings of the ACM Symposium on Applied Computing, SAC '04
, pp. 439-446
-
-
Siaterlis, C.1
Maglaris, B.2
-
80
-
-
84864058259
-
Factorial switching Kalman filters for condition monitoring in neonatal intensive care
-
C. Williams, J. Quinn, and N. McIntosh Factorial switching Kalman filters for condition monitoring in neonatal intensive care Neural Inf. Process. 2006 1513 1520
-
(2006)
Neural Inf. Process.
, pp. 1513-1520
-
-
Williams, C.1
Quinn, J.2
McIntosh, N.3
-
81
-
-
0036923209
-
Rule-based anomaly pattern detection for detecting disease outbreaks
-
Menlo Park, CA; Cambridge, MA; London, AAAI Press; MIT Press; 1999
-
W. Wong, A. Moore, G. Cooper, M. Wagner, Rule-based anomaly pattern detection for detecting disease outbreaks, in: Proceedings of the National Conference on Artificial Intelligence, Menlo Park, CA; Cambridge, MA; London, AAAI Press; MIT Press; 1999, 2002, pp. 217-223.
-
(2002)
Proceedings of the National Conference on Artificial Intelligence
, pp. 217-223
-
-
Wong, W.1
Moore, A.2
Cooper, G.3
Wagner, M.4
-
82
-
-
1942484473
-
Bayesian network anomaly pattern detection for disease outbreaks
-
AAAI Press
-
W. Wong, A. Moore, G. Cooper, M. Wagner, Bayesian network anomaly pattern detection for disease outbreaks, in: Proceedings of the 20th International Conference on Machine Learning, vol. 20, AAAI Press, 2003, pp. 808-815.
-
(2003)
Proceedings of the 20th International Conference on Machine Learning
, vol.20
, pp. 808-815
-
-
Wong, W.1
Moore, A.2
Cooper, G.3
Wagner, M.4
-
83
-
-
0037209446
-
Host-based intrusion detection using dynamic and static behavioral models
-
D.-Y. Yeung, and Y. Ding Host-based intrusion detection using dynamic and static behavioral models Pattern Recognit. 36 1 2003 229 243
-
(2003)
Pattern Recognit.
, vol.36
, Issue.1
, pp. 229-243
-
-
Yeung, D.-Y.1
Ding, Y.2
-
84
-
-
1642464756
-
A new anomaly detection method based on hierarchical HMM
-
X. Zhang, P. Fan, Z. Zhu, A new anomaly detection method based on hierarchical HMM, in: Proceedings of the 4th International Conference on Parallel and Distributed Computing, Applications and Technologies, IEEE, 2003, pp. 249-252.
-
(2003)
Proceedings of the 4th International Conference on Parallel and Distributed Computing, Applications and Technologies, IEEE
, pp. 249-252
-
-
Zhang, X.1
Fan, P.2
Zhu, Z.3
-
85
-
-
1142279663
-
An approach for fuzzy rule-base adaptation using on-line clustering
-
P. Angelov An approach for fuzzy rule-base adaptation using on-line clustering Int. J. Approx. Reason. 35 3 2004 275 289
-
(2004)
Int. J. Approx. Reason.
, vol.35
, Issue.3
, pp. 275-289
-
-
Angelov, P.1
-
88
-
-
17644365193
-
Multivariate density estimation with optimal marginal Parzen density estimation and Gaussianization
-
Machine Learning for Signal Processing XIV - Proceedings of 2004 IEEE Signal Processing Society Workshop
-
D. Erdogmus, R. Jenssen, Y. Rao, J. Principe, Multivariate density estimation with optimal marginal parzen density estimation and gaussianization, in: Proceedings of the 14th IEEE Signal Processing Society Workshop on Machine Learning for Signal Processing, IEEE, 2004, pp. 73-82. (Pubitemid 40557175)
-
(2004)
Machine Learning for Signal Processing XIV - Proceedings of the 2004 IEEE Signal Processing Society Workshop
, pp. 73-82
-
-
Erdogmus, D.1
Jenssen, R.2
Rao, Y.N.3
Principe, J.C.4
-
89
-
-
77951294698
-
Gaussian processes for object categorization
-
A. Kapoor, K. Grauman, R. Urtasun, and T. Darrell Gaussian processes for object categorization Int. J. Comput. Vis. 88 2 2010 169 188
-
(2010)
Int. J. Comput. Vis.
, vol.88
, Issue.2
, pp. 169-188
-
-
Kapoor, A.1
Grauman, K.2
Urtasun, R.3
Darrell, T.4
-
90
-
-
79952531732
-
One-class classification with Gaussian processes
-
M. Kemmler, E. Rodner, J. Denzler, One-class classification with Gaussian processes, in: Asian Conference on Computer Vision (ACCV), vol. 6493, 2011, pp. 489-500.
-
(2011)
Asian Conference on Computer Vision (ACCV)
, vol.6493
, pp. 489-500
-
-
Kemmler, M.1
Rodner, E.2
Denzler, J.3
-
92
-
-
77955753212
-
A fast approach to novelty detection in video streams using recursive density estimation
-
R. Ramezani, P. Angelov, X. Zhou, A fast approach to novelty detection in video streams using recursive density estimation, in: Proceedings of the 4th International IEEE Conference Intelligent Systems, IS'08, IEEE, vol. 2, 2008, pp. 14-22.
-
(2008)
Proceedings of the 4th International IEEE Conference Intelligent Systems, IS'08, IEEE
, vol.2
, pp. 14-22
-
-
Ramezani, R.1
Angelov, P.2
Zhou, X.3
-
93
-
-
35248830261
-
Online outlier detection in sensor data using non-parametric models
-
S. Subramaniam, T. Palpanas, D. Papadopoulos, V. Kalogeraki, D. Gunopulos, Online outlier detection in sensor data using non-parametric models, in: Proceedings of the 32nd International Conference on Very Large Databases, VLDB Endowment, 2006, pp. 187-198.
-
(2006)
Proceedings of the 32nd International Conference on Very Large Databases, VLDB Endowment
, pp. 187-198
-
-
Subramaniam, S.1
Palpanas, T.2
Papadopoulos, D.3
Kalogeraki, V.4
Gunopulos, D.5
-
94
-
-
33745725165
-
Biosign™: Multi-parameter monitoring for early warning of patient deterioration
-
L. Tarassenko, A. Hann, A. Patterson, E. Braithwaite, K. Davidson, V. Barber, D. Young, Biosign™: multi-parameter monitoring for early warning of patient deterioration, in: Proceedings of the 3rd IEE International Seminar on Medical Applications of Signal Processing, IET, 2005, pp. 71-76.
-
(2005)
Proceedings of the 3rd IEE International Seminar on Medical Applications of Signal Processing, IET
, pp. 71-76
-
-
Tarassenko, L.1
Hann, A.2
Patterson, A.3
Braithwaite, E.4
Davidson, K.5
Barber, V.6
Young, D.7
-
95
-
-
33745713040
-
Integrated monitoring and analysis for early warning of patient deterioration
-
L. Tarassenko, A. Hann, and D. Young Integrated monitoring and analysis for early warning of patient deterioration Br. J. Anaesth. 97 1 2006 64 68
-
(2006)
Br. J. Anaesth.
, vol.97
, Issue.1
, pp. 64-68
-
-
Tarassenko, L.1
Hann, A.2
Young, D.3
-
97
-
-
0142063808
-
Parzen-window network intrusion detectors
-
D. Yeung, C. Chow, Parzen-window network intrusion detectors, in: Proceedings of the 16th International Conference on Pattern Recognition, vol. 4, IEEE, 2002, pp. 385-388. (Pubitemid 44851023)
-
(2002)
Proceedings - International Conference on Pattern Recognition
, vol.16
, Issue.4
, pp. 385-388
-
-
Yeung, D.-Y.1
Chow, C.2
-
98
-
-
84901453196
-
Anomaly detection in multidimensional data using negative selection algorithm
-
IEEE
-
D. Dasgupta, N. Majumdar, Anomaly detection in multidimensional data using negative selection algorithm, in: Proceedings of the Congress on Evolutionary Computation (CEC), vol. 2, IEEE, 2002, pp. 1039-1044.
-
(2002)
Proceedings of the Congress on Evolutionary Computation (CEC)
, vol.2
, pp. 1039-1044
-
-
Dasgupta, D.1
Majumdar, N.2
-
100
-
-
0038537231
-
An immuno-fuzzy approach to anomaly detection
-
J. Gómez, F. González, D. Dasgupta, An immuno-fuzzy approach to anomaly detection, in: 12th IEEE International Conference on Fuzzy Systems (FUZZ '03), vol. 2, 2003, pp. 1219-1224.
-
(2003)
12th IEEE International Conference on Fuzzy Systems (FUZZ '03)
, vol.2
, pp. 1219-1224
-
-
Gómez, J.1
-
101
-
-
3543106606
-
Anomaly detection using real-valued negative selection
-
DOI 10.1023/A:1026195112518
-
F. González, and D. Dasgupta Anomaly detection using real-valued negative selection Genet. Program. Evolvable Mach. 4 4 2003 383 403 (Pubitemid 37283494)
-
(2003)
Genetic Programming And Evolvable Machines
, vol.4
, Issue.4
, pp. 383-403
-
-
Gonzalez, F.A.1
Dasgupta, D.2
-
102
-
-
35248825596
-
An investigation of the negative selection algorithm for fault detection in refrigeration systems
-
D. Taylor, and D. Corne An investigation of the negative selection algorithm for fault detection in refrigeration systems Artif. Immune Syst. 2787 2003 34 45
-
(2003)
Artif. Immune Syst.
, vol.2787
, pp. 34-45
-
-
Taylor, D.1
Corne, D.2
-
105
-
-
27544508958
-
A gamma mixture model better accounts for among site rate heterogeneity
-
I. Mayrose, N. Friedman, and T. Pupko A gamma mixture model better accounts for among site rate heterogeneity Bioinformatics 21 2 2005 151 158
-
(2005)
Bioinformatics
, vol.21
, Issue.2
, pp. 151-158
-
-
Mayrose, I.1
Friedman, N.2
Pupko, T.3
-
106
-
-
34247850854
-
Modelling nonlinear count time series with local mixtures of Poisson autoregressions
-
DOI 10.1016/j.csda.2006.09.032, PII S0167947306003586
-
A. Carvalho, and M. Tanner Modelling nonlinear count time series with local mixtures of poisson autoregressions Comput. Stat. Data Anal. 51 11 2007 5266 5294 (Pubitemid 46694026)
-
(2007)
Computational Statistics and Data Analysis
, vol.51
, Issue.11
, pp. 5266-5294
-
-
Carvalho, A.X.1
Tanner, M.A.2
-
107
-
-
15844362098
-
Robust Bayesian mixture modelling
-
DOI 10.1016/j.neucom.2004.11.018, PII S0925231204005181
-
M. Svensén, and C. Bishop Robust Bayesian mixture modelling Neurocomputing 64 2005 235 252 (Pubitemid 40425321)
-
(2005)
Neurocomputing
, vol.64
, Issue.1-4 SPEC. ISS.
, pp. 235-252
-
-
Svensen, M.1
Bishop, C.M.2
-
108
-
-
84899914401
-
A multi-agent simulation system for prediction and scheduling of aero engine overhaul
-
A. Stranjak, P. Dutta, M. Ebden, A. Rogers, P. Vytelingum, A multi-agent simulation system for prediction and scheduling of aero engine overhaul, in: Proceedings of the 7th International Joint Conference on Autonomous Agents and Multiagent Systems: Industrial Track, International Foundation for Autonomous Agents and Multiagent Systems, 2008, pp. 81-88.
-
(2008)
Proceedings of the 7th International Joint Conference on Autonomous Agents and Multiagent Systems: Industrial Track, International Foundation for Autonomous Agents and Multiagent Systems
, pp. 81-88
-
-
Stranjak, A.1
Dutta, P.2
Ebden, M.3
Rogers, A.4
Vytelingum, P.5
-
109
-
-
0000184052
-
Statistical independence and novelty detection with information preserving nonlinear maps
-
L. Parra, G. Deco, and S. Miesbach Statistical independence and novelty detection with information preserving nonlinear maps Neural Comput. 8 2 1996 260 269 (Pubitemid 126449927)
-
(1996)
Neural Computation
, vol.8
, Issue.2
, pp. 260-269
-
-
Parra, L.1
Deco, G.2
Miesbach, S.3
-
110
-
-
0030657262
-
Choosing an appropriate model for novelty detection
-
A. Nairac, T. Corbett-Clark, R. Ripley, N. Townsend, L. Tarassenko, Choosing an appropriate model for novelty detection, in: Proceedings of the 5th International Conference on Artificial Neural Networks, IET, 1997, pp. 117-122.
-
(1997)
Proceedings of the 5th International Conference on Artificial Neural Networks, IET
, pp. 117-122
-
-
Nairac, A.1
Corbett-Clark, T.2
Ripley, R.3
Townsend, N.4
Tarassenko, L.5
-
111
-
-
0030327833
-
Computing and graphing highest density regions
-
R. Hyndman Computing and graphing highest density regions Am. Stat. 50 2 1996 120 126
-
(1996)
Am. Stat.
, vol.50
, Issue.2
, pp. 120-126
-
-
Hyndman, R.1
-
112
-
-
0001075431
-
Statistical inference using extreme order statistics
-
J. Pickands Statistical inference using extreme order statistics Ann. Stat. 3 1 1975 119 131
-
(1975)
Ann. Stat.
, vol.3
, Issue.1
, pp. 119-131
-
-
Pickands, J.1
-
114
-
-
84958156266
-
Limiting forms of the frequency distribution of the largest or smallest member of a sample
-
Cambridge University Press
-
R. Fisher, L. Tippett, Limiting forms of the frequency distribution of the largest or smallest member of a sample, in: Proceedings of the Cambridge Philosophical Society, vol. 24, Cambridge University Press, 1928, pp. 180-190.
-
(1928)
Proceedings of the Cambridge Philosophical Society
, vol.24
, pp. 180-190
-
-
Fisher, R.1
Tippett, L.2
-
115
-
-
49349096909
-
Bayesian extreme value statistics for novelty detection in gas-turbine engines
-
D. Clifton, L. Tarassenko, N. McGrogan, D. King, S. King, P. Anuzis, Bayesian extreme value statistics for novelty detection in gas-turbine engines, in: Proceedings of the IEEE Aerospace Conference, IEEE, 2008, pp. 1-11.
-
(2008)
Proceedings of the IEEE Aerospace Conference, IEEE
, pp. 1-11
-
-
Clifton, D.1
Tarassenko, L.2
McGrogan, N.3
King, D.4
King, S.5
Anuzis, P.6
-
116
-
-
0037248049
-
Experimental validation of a structural health monitoring methodology part i. Novelty detection on a laboratory structure
-
K. Worden, G. Manson, and D. Allman Experimental validation of a structural health monitoring methodology part i. Novelty detection on a laboratory structure J. Sound Vib. 259 2 2003 323 343
-
(2003)
J. Sound Vib.
, vol.259
, Issue.2
, pp. 323-343
-
-
Worden, K.1
Manson, G.2
Allman, D.3
-
117
-
-
3543125360
-
On-line unsupervised outlier detection using finite mixtures with discounting learning algorithms
-
DOI 10.1023/B:DAMI.0000023676.72185.7c
-
K. Yamanishi, J. Takeuchi, G. Williams, and P. Milne On-line unsupervised outlier detection using finite mixtures with discounting learning algorithms Data Min. Knowl. Discov. 8 3 2004 275 300 (Pubitemid 39019964)
-
(2004)
Data Mining and Knowledge Discovery
, vol.8
, Issue.3
, pp. 275-300
-
-
Yamanishi, K.1
Takeuchi, J.-I.2
Williams, G.3
Milne, P.4
-
118
-
-
0034592923
-
On-line unsupervised outlier detection using finite mixtures with discounting learning algorithms
-
K. Yamanishi, J. Takeuchi, G. Williams, P. Milne, On-line unsupervised outlier detection using finite mixtures with discounting learning algorithms, in: Proceedings of the 6th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), ACM, 2000, pp. 320-324.
-
(2000)
Proceedings of the 6th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), ACM
, pp. 320-324
-
-
Yamanishi, K.1
Takeuchi, J.2
Williams, G.3
Milne, P.4
-
119
-
-
34548577511
-
An Empirical Bayes approach to detect anomalies in dynamic multidimensional arrays
-
DOI 10.1109/ICDM.2005.22, 1565658, Proceedings - Fifth IEEE International Conference on Data Mining, ICDM 2005
-
D. Agarwal, An empirical Bayes approach to detect anomalies in dynamic multidimensional arrays, in: Proceedings of the 5th IEEE International Conference on Data Mining, IEEE, 2005, pp. 26-33. (Pubitemid 47385673)
-
(2005)
Proceedings - IEEE International Conference on Data Mining, ICDM
, pp. 26-33
-
-
Agarwal, D.1
-
120
-
-
33845323774
-
Detecting anomalies in cross-classified streams: A Bayesian approach
-
DOI 10.1007/s10115-006-0036-4
-
D. Agarwal Detecting anomalies in cross-classified streams a Bayesian approach Knowl. Inf. Syst. 11 1 2007 29 44 (Pubitemid 44867020)
-
(2007)
Knowledge and Information Systems
, vol.11
, Issue.1
, pp. 29-44
-
-
Agarwal, D.1
-
121
-
-
0037349382
-
Using novelty detection to identify abnormalities caused by mean shifts in bivariate processes
-
F. Zorriassatine, J. Tannock, and C. O'Brien Using novelty detection to identify abnormalities caused by mean shifts in bivariate processes Comput. Ind. Eng. 44 3 2003 385 408
-
(2003)
Comput. Ind. Eng.
, vol.44
, Issue.3
, pp. 385-408
-
-
Zorriassatine, F.1
Tannock, J.2
O'Brien, C.3
-
122
-
-
0001387715
-
Mean-field approaches to independent component analysis
-
P. Højen-Sørensen, O. Winther, and L. Hansen Mean-field approaches to independent component analysis Neural Comput. 14 4 2002 889 918
-
(2002)
Neural Comput.
, vol.14
, Issue.4
, pp. 889-918
-
-
Højen-Sørensen, P.1
Winther, O.2
Hansen, L.3
-
123
-
-
0037317897
-
Efficient greedy learning of gaussian mixture models
-
DOI 10.1162/089976603762553004
-
J. Verbeek, N. Vlassis, and B. Kröse Efficient greedy learning of Gaussian mixture models Neural Comput. 15 2 2003 469 485 (Pubitemid 37049830)
-
(2003)
Neural Computation
, vol.15
, Issue.2
, pp. 469-485
-
-
Verbeek, J.J.1
Vlassis, N.2
Krose, B.3
-
124
-
-
84898950747
-
A probabilistic model for online document clustering with application to novelty detection
-
J. Zhang, Z. Ghahramani, Y. Yang, A probabilistic model for online document clustering with application to novelty detection, in: NIPS, 2005.
-
(2005)
NIPS
-
-
Zhang, J.1
Ghahramani, Z.2
Yang, Y.3
-
125
-
-
58249143167
-
Concepts for novelty detection and handling based on a case-based reasoning process scheme
-
P. Perner Concepts for novelty detection and handling based on a case-based reasoning process scheme Eng. Appl. Artif. Intell. 22 1 2009 86 91
-
(2009)
Eng. Appl. Artif. Intell.
, vol.22
, Issue.1
, pp. 86-91
-
-
Perner, P.1
-
126
-
-
56049119915
-
One-class classification by combining density and class probability estimation
-
W. Daelemans, B. Goethals, K. Morik, Springer Berlin/Heidelberg
-
K. Hempstalk, E. Frank, and I. Witten One-class classification by combining density and class probability estimation W. Daelemans, B. Goethals, K. Morik, Machine Learning and Knowledge Discovery in Databases, Lecture Notes in Computer Science vol. 5211 2008 Springer Berlin/Heidelberg 505 519
-
(2008)
Machine Learning and Knowledge Discovery in Databases, Lecture Notes in Computer Science
, vol.5211 VOL.
, pp. 505-519
-
-
Hempstalk, K.1
Frank, E.2
Witten, I.3
-
128
-
-
68949141755
-
A least-squares approach to direct importance estimation
-
T. Kanamori, S. Hido, and M. Sugiyama A least-squares approach to direct importance estimation J. Mach. Learn. Res. 10 2009 1391 1445
-
(2009)
J. Mach. Learn. Res.
, vol.10
, pp. 1391-1445
-
-
Kanamori, T.1
Hido, S.2
Sugiyama, M.3
-
129
-
-
78651496720
-
Statistical outlier detection using direct density ratio estimation
-
S. Hido, Y. Tsuboi, H. Kashima, M. Sugiyama, and T. Kanamori Statistical outlier detection using direct density ratio estimation Knowl. Inf. Syst. 26 2 2011 309 336
-
(2011)
Knowl. Inf. Syst.
, vol.26
, Issue.2
, pp. 309-336
-
-
Hido, S.1
Tsuboi, Y.2
Kashima, H.3
Sugiyama, M.4
Kanamori, T.5
-
131
-
-
0036891410
-
On-line novelty detection for artefact identification in automatic anaesthesia record keeping
-
DOI 10.1016/S1350-4533(02)00146-7, PII S1350453302001467
-
S. Hoare, D. Asbridge, and P. Beatty On-line novelty detection for artefact identification in automatic anaesthesia record keeping Med. Eng. Phys. 24 10 2002 673 681 (Pubitemid 35379944)
-
(2002)
Medical Engineering and Physics
, vol.24
, Issue.10
, pp. 673-681
-
-
Hoare, S.W.1
Asbridge, D.2
Beatty, P.C.W.3
-
132
-
-
0001614845
-
A probabilistic resource allocating network for novelty detection
-
S. Roberts, and L. Tarassenko A probabilistic resource allocating network for novelty detection Neural Comput. 6 2 1994 270 284
-
(1994)
Neural Comput.
, vol.6
, Issue.2
, pp. 270-284
-
-
Roberts, S.1
Tarassenko, L.2
-
133
-
-
33745652986
-
Outlier detection in multivariate time series by projection pursuit
-
DOI 10.1198/016214505000001131
-
P. Galeano, D. Peña, and R. Tsay Outlier detection in multivariate time series by projection pursuit J. Am. Stat. Assoc. 101 474 2006 654 669 (Pubitemid 43972306)
-
(2006)
Journal of the American Statistical Association
, vol.101
, Issue.474
, pp. 654-669
-
-
Galeano, P.1
Pena, D.2
Tsay, R.S.3
-
134
-
-
14644414808
-
Simultaneous wavelength selection and outlier detection in multivariate regression of near-infrared spectra
-
DOI 10.2116/analsci.21.161
-
D. Chen, X. Shao, B. Hu, and Q. Su Simultaneous wavelength selection and outlier detection in multivariate regression of near-infrared spectra Anal. Sci. 21 2 2005 161 166 (Pubitemid 40313909)
-
(2005)
Analytical Sciences
, vol.21
, Issue.2
, pp. 161-166
-
-
Chen, D.1
Shao, X.2
Hu, B.3
Su, Q.4
-
135
-
-
33748703576
-
Detecting outlying samples in microarray data: A critical assessment of the effect of outliers on sample classification
-
K. Kadota, D. Tominaga, Y. Akiyama, and K. Takahashi Detecting outlying samples in microarray data: a critical assessment of the effect of outliers on sample classification Chem-Bio Informat. 3 1 2003 30 45
-
(2003)
Chem-Bio Informat.
, vol.3
, Issue.1
, pp. 30-45
-
-
Kadota, K.1
Tominaga, D.2
Akiyama, Y.3
Takahashi, K.4
-
136
-
-
0028724758
-
Markov monitoring with unknown states
-
P. Smyth Markov monitoring with unknown states IEEE J. Sel. Areas Commun. 12 9 1994 1600 1612
-
(1994)
IEEE J. Sel. Areas Commun.
, vol.12
, Issue.9
, pp. 1600-1612
-
-
Smyth, P.1
-
137
-
-
0034170950
-
Variational learning for switching state-space models
-
Z. Ghahramani, and G. Hinton Variational learning for switching state-space models Neural Comput. 12 4 2000 831 864
-
(2000)
Neural Comput.
, vol.12
, Issue.4
, pp. 831-864
-
-
Ghahramani, Z.1
Hinton, G.2
-
138
-
-
19544382513
-
Detection of significant sets of episodes in event sequences
-
Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004
-
M. Atallah, W. Szpankowski, R. Gwadera, Detection of significant sets of episodes in event sequences, in: Proceedings of the 4th IEEE International Conference on Data Mining, ICDM'04, IEEE, 2004, pp. 3-10. (Pubitemid 40731007)
-
(2004)
Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004
, pp. 3-10
-
-
Atallah, M.1
Gwadera, R.2
Szpankowski, W.3
-
139
-
-
26844565732
-
Active platform security through intrusion detection using naive Bayesian network for anomaly detection
-
A. Sebyala, T. Olukemi, L. Sacks, Active platform security through intrusion detection using naive Bayesian network for anomaly detection, in: London Communications Symposium, Citeseer, 2002.
-
(2002)
London Communications Symposium, Citeseer
-
-
Sebyala, A.1
Olukemi, T.2
Sacks, L.3
-
140
-
-
14844319067
-
Anomaly detection of Web-based attacks
-
Proceedings of the 10th ACM Conference on Computer and Communications Security, CCS 2003
-
C. Kruegel, G. Vigna, Anomaly detection of web-based attacks, in: Proceedings of the 10th ACM Conference on Computer and Communications Security, ACM, 2003, pp. 251-261. (Pubitemid 40673807)
-
(2003)
Proceedings of the ACM Conference on Computer and Communications Security
, pp. 251-261
-
-
Kruegel, C.1
Vigna, G.2
-
141
-
-
84944737204
-
Bayesian event classification for intrusion detection
-
C. Kruegel, D. Mutz, W. Robertson, F. Valeur, Bayesian event classification for intrusion detection, in: Proceedings of the 19th Annual Computer Security Applications Conference, IEEE, 2003, pp. 14-23.
-
(2003)
Proceedings of the 19th Annual Computer Security Applications Conference, IEEE
, pp. 14-23
-
-
Kruegel, C.1
Mutz, D.2
Robertson, W.3
Valeur, F.4
-
142
-
-
0242456801
-
Learning nonstationary models of normal network traffic for detecting novel attacks
-
M. Mahoney, P. Chan, Learning nonstationary models of normal network traffic for detecting novel attacks, in: Proceedings of the 8th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), ACM, 2002, pp. 376-385.
-
(2002)
Proceedings of the 8th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), ACM
, pp. 376-385
-
-
Mahoney, M.1
Chan, P.2
-
143
-
-
0001473437
-
On estimation of a probability density function and mode
-
E. Parzen On estimation of a probability density function and mode Ann. Math. Stat. 33 3 1962 1065 1076
-
(1962)
Ann. Math. Stat.
, vol.33
, Issue.3
, pp. 1065-1076
-
-
Parzen, E.1
-
145
-
-
46449103765
-
Defining the incidence of cardiorespiratory instability in patients in step-down units using an electronic integrated monitoring system
-
DOI 10.1001/archinte.168.12.1300
-
M. Hravnak, L. Edwards, A. Clontz, C. Valenta, M. DeVita, and M. Pinsky Defining the incidence of cardiorespiratory instability in patients in step-down units using an electronic integrated monitoring system Arch. Internal Med. 168 12 2008 1300 1308 (Pubitemid 351930837)
-
(2008)
Archives of Internal Medicine
, vol.168
, Issue.12
, pp. 1300-1308
-
-
Hravnak, M.1
Edwards, L.2
Clontz, A.3
Valenta, C.4
DeVita, M.A.5
Pinsky, M.R.6
-
146
-
-
0742272554
-
An approach to online identification of Takagi-Sugeno fuzzy models
-
P. Angelov, and D. Filev An approach to online identification of Takagi-Sugeno fuzzy models IEEE Trans. Syst. Man Cybern. Part B Cybern. 34 1 2004 484 498
-
(2004)
IEEE Trans. Syst. Man Cybern. Part B Cybern.
, vol.34
, Issue.1
, pp. 484-498
-
-
Angelov, P.1
Filev, D.2
-
147
-
-
70049091620
-
The Gaussian process density sampler
-
R. Adams, I. Murray, D. MacKay, The Gaussian process density sampler, in: Advances in Neural Information Processing Systems (NIPS) 21, 2009, pp. 9-16.
-
(2009)
Advances in Neural Information Processing Systems (NIPS)
, vol.21
, pp. 9-16
-
-
Adams, R.1
Murray, I.2
Mackay, D.3
-
148
-
-
0001524507
-
Procedures for reacting to a change in distribution
-
G. Lorden Procedures for reacting to a change in distribution Ann. Math. Stat. 42 6 1971 1897 1908
-
(1971)
Ann. Math. Stat.
, vol.42
, Issue.6
, pp. 1897-1908
-
-
Lorden, G.1
-
150
-
-
34547214360
-
A review and comparison of changepoint detection techniques for climate data
-
DOI 10.1175/JAM2493.1
-
J. Reeves, J. Chen, X.L. Wang, R. Lund, and Q.Q. Lu A review and comparison of changepoint detection techniques for climate data J. Appl. Meteorol. Climatol. 46 6 2007 900 915 (Pubitemid 47108795)
-
(2007)
Journal of Applied Meteorology and Climatology
, vol.46
, Issue.6
, pp. 900-915
-
-
Reeves, J.1
Chen, J.2
Wang, X.L.3
Lund, R.4
Lu, Q.Q.5
-
151
-
-
33947689693
-
Information sharing for distributed intrusion detection systems
-
DOI 10.1016/j.jnca.2005.07.004, PII S1084804505000494
-
T. Peng, C. Leckie, and K. Ramamohanarao Information sharing for distributed intrusion detection systems J. Netw. Comput. Appl. 30 3 2007 877 899 (Pubitemid 46497019)
-
(2007)
Journal of Network and Computer Applications
, vol.30
, Issue.3
, pp. 877-899
-
-
Peng, T.1
Leckie, C.2
Ramamohanarao, K.3
-
152
-
-
33745917688
-
An anomaly detection algorithm for detecting attacks in wireless sensor networks
-
Intelligence and Security Informatics - IEEE International Conference on Intelligence and Security Informatics, ISI 2006, Proceedings
-
T. Van Phuong, L. Hung, S. Cho, Y. Lee, and S. Lee An anomaly detection algorithm for detecting attacks in wireless sensor networks Intell. Secur. Informat. 3975 2006 735 736 (Pubitemid 44045658)
-
(2006)
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
, vol.3975
, pp. 735-736
-
-
Van Phuong, T.1
Hung, L.X.2
Cho, S.J.3
Lee, Y.-K.4
Lee, S.5
-
153
-
-
77952579459
-
State-Of-The-Art in Bayesian changepoint detection
-
A.G. Tartakovsky, and G.V. Moustakides State-of-the-art in Bayesian changepoint detection Seq. Anal. 29 2 2010 125 145
-
(2010)
Seq. Anal.
, vol.29
, Issue.2
, pp. 125-145
-
-
Tartakovsky, A.G.1
Moustakides, G.V.2
-
155
-
-
0027961889
-
Self-nonself discrimination in a computer
-
S. Forrest, A. Perelson, L. Allen, R. Cherukuri, Self-nonself discrimination in a computer, in: Proceedings of the IEEE Computer Society Symposium on Research in Security and Privacy, IEEE, 1994, pp. 202-212.
-
(1994)
Proceedings of the IEEE Computer Society Symposium on Research in Security and Privacy, IEEE
, pp. 202-212
-
-
Forrest, S.1
Perelson, A.2
Allen, L.3
Cherukuri, R.4
-
156
-
-
79957798213
-
Fast outlier detection in high dimensional spaces
-
Springer-Verlag, London, UK
-
F. Angiulli, C. Pizzuti, Fast outlier detection in high dimensional spaces, in: Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery, PKDD '02, Springer-Verlag, London, UK, 2002, pp. 15-26.
-
(2002)
Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery, PKDD '02
, pp. 15-26
-
-
Angiulli, F.1
Pizzuti, C.2
-
157
-
-
77952380096
-
Mining distance-based outliers in near linear time with randomization and a simple pruning rule
-
S. Bay, M. Schwabacher, Mining distance-based outliers in near linear time with randomization and a simple pruning rule, in: Proceedings of the 9th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), ACM, 2003, pp. 29-38.
-
(2003)
Proceedings of the 9th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), ACM
, pp. 29-38
-
-
Bay, S.1
Schwabacher, M.2
-
158
-
-
52649136576
-
Similarity measures for categorical data: A comparative evaluation
-
S. Boriah, V. Chandola, V. Kumar, Similarity measures for categorical data: a comparative evaluation, in: Proceedings of the 8th SIAM International Conference on Data Mining, 2008, pp. 243-254.
-
(2008)
Proceedings of the 8th SIAM International Conference on Data Mining
, pp. 243-254
-
-
Boriah, S.1
Chandola, V.2
Kumar, V.3
-
159
-
-
0039253819
-
LOF: Identifying density-based local outliers
-
ACM
-
M. Breunig, H. Kriegel, R. Ng, J. Sander, LOF: identifying density-based local outliers, in: Proceedings of the ACM SIGMOD International Conference on Management of Data, vol. 29, ACM, 2000, pp. 93-104.
-
(2000)
Proceedings of the ACM SIGMOD International Conference on Management of Data
, vol.29
, pp. 93-104
-
-
Breunig, M.1
Kriegel, H.2
Ng, R.3
Sander, J.4
-
160
-
-
70349673892
-
-
Technical Report 08-008, University of Minnesota
-
V. Chandola, S. Boriah, V. Kumar, Understanding Categorical Similarity Measures for Outlier Detection, Technical Report 08-008, University of Minnesota, 2008.
-
(2008)
Understanding Categorical Similarity Measures for Outlier Detection
-
-
Chandola, V.1
Boriah, S.2
Kumar, V.3
-
161
-
-
33645548899
-
SLOM: A new measure for local spatial outliers
-
DOI 10.1007/s10115-005-0200-2
-
S. Chawla, and P. Sun SLOM a new measure for local spatial outliers Knowl. Inf. Syst. 9 4 2006 412 429 (Pubitemid 43507459)
-
(2006)
Knowledge and Information Systems
, vol.9
, Issue.4
, pp. 412-429
-
-
Chawla, S.1
Sun, P.2
-
162
-
-
19544370003
-
LOADED: Link-based outlier and anomaly detection in evolving data sets
-
Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004
-
A. Ghoting, M. Otey, S. Parthasarathy, Loaded: link-based outlier and anomaly detection in evolving data sets, in: Proceedings of the 4th IEEE International Conference on Data Mining, ICDM'04, IEEE, 2004, pp. 387-390. (Pubitemid 40731064)
-
(2004)
Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004
, pp. 387-390
-
-
Ghoting, A.1
Otey, M.E.2
Parthasarathy, S.3
-
163
-
-
42749086305
-
Fast mining of distance-based outliers in high-dimensional datasets
-
A. Ghoting, S. Parthasarathy, and M. Otey Fast mining of distance-based outliers in high-dimensional datasets Data Min. Knowl. Discov. 16 3 2008 349 364
-
(2008)
Data Min. Knowl. Discov.
, vol.16
, Issue.3
, pp. 349-364
-
-
Ghoting, A.1
Parthasarathy, S.2
Otey, M.3
-
164
-
-
10044269754
-
Outlier detection using k-nearest neighbour graph
-
IEEE
-
V. Hautamaki, I. Karkkainen, P. Franti, Outlier detection using k-nearest neighbour graph, in: Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004, vol. 3, IEEE, 2004, pp. 430-433.
-
(2004)
Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
, vol.3
, pp. 430-433
-
-
Hautamaki, V.1
Karkkainen, I.2
Franti, P.3
-
165
-
-
33645971031
-
Outlier detection using rough set theory
-
D. Slezak, J. Yao, J. Peters, W. Ziarko, X. Hu, Springer, Berlin Heidelberg
-
F. Jiang, Y. Sui, and C. Cao Outlier detection using rough set theory D. Slezak, J. Yao, J. Peters, W. Ziarko, X. Hu, Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, Lecture Notes in Computer Science vol. 3642 2005 Springer, Berlin Heidelberg 79 87
-
(2005)
Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, Lecture Notes in Computer Science
, vol.3642 VOL.
, pp. 79-87
-
-
Jiang, F.1
Sui, Y.2
Cao, C.3
-
167
-
-
33646553013
-
Fast distributed outlier detection in mixed-attribute data sets
-
M. Otey, A. Ghoting, and S. Parthasarathy Fast distributed outlier detection in mixed-attribute data sets Data Min. Knowl. Discov. 12 2 2006 203 228
-
(2006)
Data Min. Knowl. Discov.
, vol.12
, Issue.2
, pp. 203-228
-
-
Otey, M.1
Ghoting, A.2
Parthasarathy, S.3
-
169
-
-
34548752457
-
Incremental local outlier detection for data streams
-
DOI 10.1109/CIDM.2007.368917, 4221341, Proceedings of the 2007 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2007
-
D. Pokrajac, A. Lazarevic, L. Latecki, Incremental local outlier detection for data streams, in: Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining (CIDM), IEEE, 2007, pp. 504-515. (Pubitemid 47431481)
-
(2007)
Proceedings of the 2007 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2007
, pp. 504-515
-
-
Pokrajac, D.1
Lazarevic, A.2
Latecki, L.J.3
-
170
-
-
33749564287
-
Outlier detection by sampling with accuracy guarantees
-
KDD 2006: Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
-
M. Wu, C. Jermaine, Outlier detection by sampling with accuracy guarantees, in: Proceedings of the 12th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), ACM, 2006, pp. 767-772. (Pubitemid 44535588)
-
(2006)
Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
, vol.2006
, pp. 767-772
-
-
Wu, M.1
Jermaine, C.2
-
171
-
-
33749316703
-
Detecting outlying subspaces for high-dimensional data: The new task, algorithms, and performance
-
DOI 10.1007/s10115-006-0020-z
-
J. Zhang, and H. Wang Detecting outlying subspaces for high-dimensional data the new task, and performance Knowl. Inf. Syst. 10 3 2006 333 355 (Pubitemid 44490000)
-
(2006)
Knowledge and Information Systems
, vol.10
, Issue.3
, pp. 333-355
-
-
Zhang, J.1
Wang, H.2
-
172
-
-
0038494682
-
COOLCAT: An entropy-based algorithm for categorical clustering
-
D. Barbará, Y. Li, J. Couto, COOLCAT: an entropy-based algorithm for categorical clustering, in: Proceedings of the 11th International Conference on Information and Knowledge Management, ACM, 2002, pp. 582-589.
-
(2002)
Proceedings of the 11th International Conference on Information and Knowledge Management, ACM
, pp. 582-589
-
-
Barbará, D.1
-
173
-
-
0038336923
-
Bootstrapping a data mining intrusion detection system
-
D. Barbará, Y. Li, J. Couto, J. Lin, S. Jajodia, Bootstrapping a data mining intrusion detection system, in: Proceedings of the ACM Symposium on Applied Computing, ACM, 2003, pp. 421-425.
-
(2003)
Proceedings of the ACM Symposium on Applied Computing, ACM
, pp. 421-425
-
-
Barbará, D.1
-
174
-
-
67049085174
-
-
Technical Report NASA TM-2006-214553, NASA Ames Research Center
-
S. Budalakoti, A. Srivastava, R. Akella, E. Turkov, Anomaly Detection in Large Sets of High-Dimensional Symbol Sequences, Technical Report NASA TM-2006-214553, NASA Ames Research Center, 2006.
-
(2006)
Anomaly Detection in Large Sets of High-Dimensional Symbol Sequences
-
-
Budalakoti, S.1
Srivastava, A.2
Akella, R.3
Turkov, E.4
-
175
-
-
33745878795
-
Learning shape for jet engine novelty detection
-
DOI 10.1007/11760191-121, Advances in Neural Networks - ISNN 2006: Third International Symposium on Neural Networks, ISNN 2006, Proceedings - Part III
-
D. Clifton, P. Bannister, and L. Tarassenko Learning shape for jet engine novelty detection Adv. Neural Netw. (ISNN) 3973 2006 828 835 (Pubitemid 44045792)
-
(2006)
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
, vol.3973
, pp. 828-835
-
-
Clifton, D.A.1
Bannister, P.R.2
Tarassenko, L.3
-
176
-
-
34250804775
-
A framework for novelty detection in jet engine vibration data
-
Damage Assessment of Structures VII
-
D. Clifton, P. Bannister, and L. Tarassenko A framework for novelty detection in jet engine vibration data Key Eng. Mater. 347 2007 305 310 (Pubitemid 46987334)
-
(2007)
Key Engineering Materials
, vol.347
, pp. 305-310
-
-
Clifton, D.A.1
Bannister, P.R.2
Tarassenko, L.3
-
177
-
-
77953110999
-
Applying the possibilistic c-means algorithm in kernel-induced spaces
-
M. Filippone, F. Masulli, and S. Rovetta Applying the possibilistic c-means algorithm in kernel-induced spaces IEEE Trans. Fuzzy Syst. 18 3 2010 572 584
-
(2010)
IEEE Trans. Fuzzy Syst.
, vol.18
, Issue.3
, pp. 572-584
-
-
Filippone, M.1
Masulli, F.2
Rovetta, S.3
-
178
-
-
0037410488
-
Discovering cluster-based local outliers
-
Z. He, X. Xu, and S. Deng Discovering cluster-based local outliers Pattern Recognit. Lett. 24 9 2003 1641 1650
-
(2003)
Pattern Recognit. Lett.
, vol.24
, Issue.9
, pp. 1641-1650
-
-
He, Z.1
Xu, X.2
Deng, S.3
-
179
-
-
82255179131
-
Machine learning-based novelty detection for faulty wafer detection in semiconductor manufacturing
-
D. Kim, P. Kang, S. Cho, H. Lee, and S. Doh Machine learning-based novelty detection for faulty wafer detection in semiconductor manufacturing Expert Syst. Appl. 39 4 2011 4075 4083
-
(2011)
Expert Syst. Appl.
, vol.39
, Issue.4
, pp. 4075-4083
-
-
Kim, D.1
Kang, P.2
Cho, S.3
Lee, H.4
Doh, S.5
-
180
-
-
33751524073
-
Discovering recurring anomalies in text reports regarding complex space systems
-
A. Srivastava, B. Zane-Ulman, Discovering recurring anomalies in text reports regarding complex space systems, in: Proceedings of the IEEE Aerospace Conference, IEEE, 2005, pp. 3853-3862.
-
(2005)
Proceedings of the IEEE Aerospace Conference, IEEE
, pp. 3853-3862
-
-
Srivastava, A.1
Zane-Ulman, B.2
-
181
-
-
70349676147
-
Enabling the discovery of recurring anomalies in aerospace problem reports using high-dimensional clustering techniques
-
A. Srivastava, Enabling the discovery of recurring anomalies in aerospace problem reports using high-dimensional clustering techniques, in: Proceedings of the IEEE Aerospace Conference, IEEE, 2006, pp. 1-17.
-
(2006)
Proceedings of the IEEE Aerospace Conference, IEEE
, pp. 1-17
-
-
Srivastava, A.1
-
182
-
-
35048823911
-
CD-trees an efficient index structure for outlier detection
-
H. Sun, Y. Bao, F. Zhao, G. Yu, and D. Wang CD-trees an efficient index structure for outlier detection Adv. Web-Age Inf. Manage. 3129 2004 600 609
-
(2004)
Adv. Web-Age Inf. Manage.
, vol.3129
, pp. 600-609
-
-
Sun, H.1
Bao, Y.2
Zhao, F.3
Yu, G.4
Wang, D.5
-
183
-
-
84983043998
-
Identifying high-risk patients without labeled training data: Anomaly detection methodologies to predict adverse outcomes
-
Z. Syed, M. Saeed, I. Rubinfeld, Identifying high-risk patients without labeled training data: anomaly detection methodologies to predict adverse outcomes, in: AMIA Annual Symposium Proceedings, vol. 2010, American Medical Informatics Association, 2010, pp. 772-776.
-
(2010)
AMIA Annual Symposium Proceedings, Vol. 2010, American Medical Informatics Association
, pp. 772-776
-
-
Syed, Z.1
Saeed, M.2
Rubinfeld, I.3
-
184
-
-
56349122418
-
Outlier identification and market segmentation using kernel-based clustering techniques
-
C.-H. Wang Outlier identification and market segmentation using kernel-based clustering techniques Exp. Syst. Appl. 36 2 2009 3744 3750
-
(2009)
Exp. Syst. Appl.
, vol.36
, Issue.2
, pp. 3744-3750
-
-
Wang, C.-H.1
-
185
-
-
0345359233
-
CLUSEQ: Efficient and effective sequence clustering
-
J. Yang, W. Wang, CLUSEQ: efficient and effective sequence clustering, in: Proceedings of the 19th International Conference on Data Engineering, IEEE, 2003, pp. 101-112.
-
(2003)
Proceedings of the 19th International Conference on Data Engineering, IEEE
, pp. 101-112
-
-
Yang, J.1
Wang, W.2
-
186
-
-
84861610344
-
Novelty detection in wildlife scenes through semantic context modelling
-
S.-P. Yong, J.D. Deng, and M.K. Purvis Novelty detection in wildlife scenes through semantic context modelling Pattern Recognit. 45 9 2012 3439 3450
-
(2012)
Pattern Recognit.
, vol.45
, Issue.9
, pp. 3439-3450
-
-
Yong, S.-P.1
Deng, J.D.2
Purvis, M.K.3
-
187
-
-
84893219608
-
Wildlife video key-frame extraction based on novelty detection in semantic context
-
S. Yong, J. Deng, and M. Purvis Wildlife video key-frame extraction based on novelty detection in semantic context Multimed. Tools Appl. 62 2 2013 359 376
-
(2013)
Multimed. Tools Appl.
, vol.62
, Issue.2
, pp. 359-376
-
-
Yong, S.1
Deng, J.2
Purvis, M.3
-
188
-
-
85132247975
-
Findout finding outliers in very large datasets
-
D. Yu, G. Sheikholeslami, and A. Zhang Findout finding outliers in very large datasets Knowl. Inf. Syst. 4 4 2002 387 412
-
(2002)
Knowl. Inf. Syst.
, vol.4
, Issue.4
, pp. 387-412
-
-
Yu, D.1
Sheikholeslami, G.2
Zhang, A.3
-
189
-
-
38049044112
-
Unsupervised outlier detection in sensor networks using aggregation tree
-
K. Zhang, S. Shi, H. Gao, and J. Li Unsupervised outlier detection in sensor networks using aggregation tree Adv. Data Min. Appl. 4632 2007 158 169
-
(2007)
Adv. Data Min. Appl.
, vol.4632
, pp. 158-169
-
-
Zhang, K.1
Shi, S.2
Gao, H.3
Li, J.4
-
190
-
-
0002948319
-
Algorithms for mining distance-based outliers in large datasets
-
E. Knorr, R. Ng, Algorithms for mining distance-based outliers in large datasets, in: Proceedings of the International Conference on Very Large Data Bases, Citeseer, 1998, pp. 392-403.
-
(1998)
Proceedings of the International Conference on Very Large Data Bases, Citeseer
, pp. 392-403
-
-
Knorr, E.1
Ng, R.2
-
191
-
-
33749567862
-
Mining distance-based outliers from large databases in any metric space
-
KDD 2006: Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
-
Y. Tao, X. Xiao, S. Zhou, Mining distance-based outliers from large databases in any metric space, in: Proceedings of the 12th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), ACM, 2006, pp. 394-403. (Pubitemid 44535536)
-
(2006)
Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
, vol.2006
, pp. 394-403
-
-
Tao, Y.1
Xiao, X.2
Zhou, S.3
-
192
-
-
27144498604
-
Hot: Hypergraph-based outlier test for categorical data
-
L. Wei, W. Qian, A. Zhou, W. Jin, and J. Yu Hot: hypergraph-based outlier test for categorical data Adv. Knowl. Discov. Data Min. 2637 2003 562
-
(2003)
Adv. Knowl. Discov. Data Min.
, vol.2637
, pp. 562
-
-
Wei, L.1
Qian, W.2
Zhou, A.3
Jin, W.4
Yu, J.5
-
193
-
-
0001882616
-
Fast algorithms for mining association rules
-
R. Agrawal, R. Srikant, Fast algorithms for mining association rules, in: Proceedings of the 20th International Conference on Very Large Data Bases, VLDB, vol. 1215, 1994, pp. 487-499.
-
(1994)
Proceedings of the 20th International Conference on Very Large Data Bases, VLDB
, vol.1215
, pp. 487-499
-
-
Agrawal, R.1
Srikant, R.2
-
194
-
-
0345359208
-
LOCI: Fast outlier detection using the local correlation integral
-
S. Papadimitriou, H. Kitagawa, P. Gibbons, C. Faloutsos, LOCI: fast outlier detection using the local correlation integral, in: Proceedings of the 19th International Conference on Data Engineering, IEEE, 2003, pp. 315-326.
-
(2003)
Proceedings of the 19th International Conference on Data Engineering, IEEE
, pp. 315-326
-
-
Papadimitriou, S.1
Kitagawa, H.2
Gibbons, P.3
Faloutsos, C.4
-
195
-
-
84879085576
-
Enhancements on local outlier detection
-
A. Chiu, A. Fu, Enhancements on local outlier detection, in: Proceedings of the 7th International Database Engineering and Applications Symposium, IEEE, 2003, pp. 298-307.
-
(2003)
Proceedings of the 7th International Database Engineering and Applications Symposium, IEEE
, pp. 298-307
-
-
Chiu, A.1
Fu, A.2
-
196
-
-
84945281435
-
Enhancing effectiveness of outlier detections for low density patterns
-
J. Tang, Z. Chen, A. Fu, and D. Cheung Enhancing effectiveness of outlier detections for low density patterns Adv. Knowl. Discov. Data Min. 2336 2002 535 548
-
(2002)
Adv. Knowl. Discov. Data Min.
, vol.2336
, pp. 535-548
-
-
Tang, J.1
Chen, Z.2
Fu, A.3
Cheung, D.4
-
197
-
-
19544366584
-
RDF: A density-based outlier detection method using vertical data representation
-
Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004
-
D. Ren, B. Wang, W. Perrizo, RDF: a density-based outlier detection method using vertical data representation, in: Proceedings of the 4th IEEE International Conference on Data Mining, ICDM'04, IEEE, 2004, pp. 503-506. (Pubitemid 40731093)
-
(2004)
Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004
, pp. 503-506
-
-
Ren, D.1
Wang, B.2
Perrizo, W.3
-
198
-
-
33645552151
-
Finding centric local outliers in categorical/numerical spaces
-
DOI 10.1007/s10115-005-0197-6
-
J. Yu, W. Qian, H. Lu, and A. Zhou Finding centric local outliers in categorical/numerical spaces Knowl. Inf. Syst. 9 3 2006 309 338 (Pubitemid 43507136)
-
(2006)
Knowledge and Information Systems
, vol.9
, Issue.3
, pp. 309-338
-
-
Yu, J.X.1
Qian, W.2
Lu, H.3
Zhou, A.4
-
199
-
-
33845240405
-
Capabilities of outlier detection schemes in large datasets, framework and methodologies
-
DOI 10.1007/s10115-005-0233-6
-
J. Tang, Z. Chen, A. Fu, and D. Cheung Capabilities of outlier detection in large datasets, framework and methodologies Knowl. Inf. Syst. 11 1 2007 45 84 (Pubitemid 44857542)
-
(2007)
Knowledge and Information Systems
, vol.11
, Issue.1
, pp. 45-84
-
-
Tang, J.1
Chen, Z.2
Fu, A.W.3
Cheung, D.W.4
-
200
-
-
19544393356
-
On local spatial outliers
-
Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004
-
P. Sun, S. Chawla, On local spatial outliers, in: Proceedings of the 4th IEEE International Conference on Data Mining, IEEE, 2004, pp. 209-216. (Pubitemid 40731033)
-
(2004)
Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004
, pp. 209-216
-
-
Sun, P.1
Chawla, S.2
-
201
-
-
33745447341
-
Mining for outliers in sequential databases
-
Society for Industrial Mathematics
-
P. Sun, S. Chawla, B. Arunasalam, Mining for outliers in sequential databases, in: Proceedings of the 6th SIAM International Conference on Data Mining, vol. 124, Society for Industrial Mathematics, 2006.
-
(2006)
Proceedings of the 6th SIAM International Conference on Data Mining
, vol.124
-
-
Sun, P.1
Chawla, S.2
Arunasalam, B.3
-
202
-
-
84872384093
-
-
Technical Report, Department of Computer Science, Florida Institute Technology Melbourne
-
P. Chan, M. Mahoney, M. Arshad, A Machine Learning Approach to Anomaly Detection, Technical Report, Department of Computer Science, Florida Institute Technology Melbourne, 2003.
-
(2003)
A Machine Learning Approach to Anomaly Detection
-
-
Chan, P.1
Mahoney, M.2
Arshad, M.3
-
203
-
-
0004008854
-
-
Kluwer Academic Publishers, Norwell, MA, USA
-
J.C. Bezdek, Pattern Recognition with Fuzzy Objective Function Algorithms, Kluwer Academic Publishers, Norwell, MA, USA, 1981.
-
(1981)
Pattern Recognition with Fuzzy Objective Function Algorithms
-
-
Bezdek, J.C.1
-
207
-
-
84946407413
-
Factor analysis based anomaly detection
-
N. Wu, J. Zhang, Factor analysis based anomaly detection, in: Proceedings of the Information Assurance Workshop, IEEE Systems, Man and Cybernetics Society, IEEE, 2003, pp. 108-115.
-
(2003)
Proceedings of the Information Assurance Workshop, IEEE Systems, Man and Cybernetics Society, IEEE
, pp. 108-115
-
-
Wu, N.1
Zhang, J.2
-
208
-
-
40349086675
-
Finding topics in collections of documents a shared nearest neighbor approach
-
L. Ertöz, M. Steinbach, and V. Kumar Finding topics in collections of documents a shared nearest neighbor approach Clust. Inf. Retr. 11 2003 83 103
-
(2003)
Clust. Inf. Retr.
, vol.11
, pp. 83-103
-
-
Ertöz, L.1
Steinbach, M.2
Kumar, V.3
-
209
-
-
84898941932
-
Support vector method for novelty detection
-
B. Schölkopf, R. Williamson, A. Smola, J. Shawe-Taylor, and J. Platt Support vector method for novelty detection Adv. Neural Inf. Process. Syst. 12 3 2000 582 588
-
(2000)
Adv. Neural Inf. Process. Syst.
, vol.12
, Issue.3
, pp. 582-588
-
-
Schölkopf, B.1
Williamson, R.2
Smola, A.3
Shawe-Taylor, J.4
Platt, J.5
-
210
-
-
79957676241
-
Unsupervised distributed novelty detection on scientific simulation data
-
J. Zhou, Y. Fu, C. Sun, and Y. Fang Unsupervised distributed novelty detection on scientific simulation data J. Comput. Inf. Syst. 7 5 2011 1533 1540
-
(2011)
J. Comput. Inf. Syst.
, vol.7
, Issue.5
, pp. 1533-1540
-
-
Zhou, J.1
Fu, Y.2
Sun, C.3
Fang, Y.4
-
211
-
-
66949153623
-
Novelty detection with application to data streams
-
E. Spinosa, A. deLeon, F. de Carvalho, and J. Gama Novelty detection with application to data streams Intell. Data Anal. 13 3 2009 405 422
-
(2009)
Intell. Data Anal.
, vol.13
, Issue.3
, pp. 405-422
-
-
Spinosa, E.1
Deleon, A.2
De Carvalho, F.3
Gama, J.4
-
213
-
-
49749143714
-
Computing correlation anomaly scores using stochastic nearest neighbors
-
T. Idé, S. Papadimitriou, M. Vlachos, Computing correlation anomaly scores using stochastic nearest neighbors, in: Proceedings of the 7th IEEE International Conference on Data Mining (ICDM), IEEE, 2007, pp. 523-528.
-
(2007)
Proceedings of the 7th IEEE International Conference on Data Mining (ICDM), IEEE
, pp. 523-528
-
-
Idé, T.1
-
214
-
-
70350656339
-
Tangent: A novel,'surprise me', recommendation algorithm
-
K. Onuma, H. Tong, C. Faloutsos, Tangent: a novel,'surprise me', recommendation algorithm, in: Proceedings of the 15th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), ACM, 2009, pp. 657-666.
-
(2009)
Proceedings of the 15th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), ACM
, pp. 657-666
-
-
Onuma, K.1
Tong, H.2
Faloutsos, C.3
-
215
-
-
0037143140
-
Neural network classification and novelty detection
-
DOI 10.1080/01431160110055804
-
M. Augusteijn, and B. Folkert Neural network classification and novelty detection Int. J. Remote Sens. 23 14 2002 2891 2902 (Pubitemid 34825152)
-
(2002)
International Journal of Remote Sensing
, vol.23
, Issue.14
, pp. 2891-2902
-
-
Augusteijn, M.F.1
Folkert, B.A.2
-
216
-
-
2142828547
-
An approach to novelty detection applied to the classification of image regions
-
S. Singh, and M. Markou An approach to novelty detection applied to the classification of image regions IEEE Trans. Knowl. Data Eng. 16 4 2004 396 407
-
(2004)
IEEE Trans. Knowl. Data Eng.
, vol.16
, Issue.4
, pp. 396-407
-
-
Singh, S.1
Markou, M.2
-
217
-
-
0036057531
-
A tale of two filters - on-line novelty detection
-
P. Crook, S. Marsland, G. Hayes, U. Nehmzow, A tale of two filters-on-line novelty detection, in: Proceedings of the IEEE International Conference on Robotics and Automation, ICRA'02, vol. 4, IEEE, 2002, pp. 3894-3899. (Pubitemid 34916147)
-
(2002)
Proceedings - IEEE International Conference on Robotics and Automation
, vol.4
, pp. 3894-3899
-
-
Crook, P.A.1
Marsland, S.2
Hayes, G.3
Nehmzow, U.4
-
218
-
-
0036082925
-
Residual generation and visualization for understanding novel process conditions
-
I. Diaz, J. Hollmen, Residual generation and visualization for understanding novel process conditions, in: Proceedings of the International Joint Conference on Neural Networks, IJCNN'02, vol. 3, IEEE, 2002, pp. 2070-2075. (Pubitemid 34647950)
-
(2002)
Proceedings of the International Joint Conference on Neural Networks
, vol.3
, pp. 2070-2075
-
-
Diaz, I.1
Hollmen, J.2
-
220
-
-
0034825091
-
Supervised versus unsupervised binary-learning by feedforward neural networks
-
DOI 10.1023/A:1007660820062
-
N. Japkowicz Supervised versus unsupervised binary-learning by feedforward neural networks Mach. Learn. 42 1 2001 97 122 (Pubitemid 32872400)
-
(2001)
Machine Learning
, vol.42
, Issue.1-2
, pp. 97-122
-
-
Japkowicz, N.1
-
221
-
-
33847410597
-
One-class document classification via Neural Networks
-
DOI 10.1016/j.neucom.2006.05.013, PII S092523120600261X, Advances in Computational Intelligence and Learning 14th European Symposium on Artificial Neural Networks 2006
-
L. Manevitz, and M. Yousef One-class document classification via neural networks Neurocomputing 70 7 2007 1466 1481 (Pubitemid 46336763)
-
(2007)
Neurocomputing
, vol.70
, Issue.7-9
, pp. 1466-1481
-
-
Manevitz, L.1
Yousef, M.2
-
222
-
-
0036079885
-
Implicit learning in autoencoder novelty assessment
-
B. Thompson, R. Marks, J. Choi, M. El-Sharkawi, M. Huang, C. Bunje, Implicit learning in autoencoder novelty assessment, in: Proceedings of the International Joint Conference on Neural Networks, IJCNN'02, vol. 3, IEEE, 2002, pp. 2878-2883. (Pubitemid 34648089)
-
(2002)
Proceedings of the International Joint Conference on Neural Networks
, vol.3
, pp. 2878-2883
-
-
Thompson, B.B.1
Marks II, R.J.2
Choi, J.J.3
El-Sharkawi, M.A.4
Huang, M.-Y.5
Bunje, C.6
-
223
-
-
27144452309
-
A comparative study of RNN for outlier detection in data mining
-
IEEE
-
G. Williams, R. Baxter, H. He, S. Hawkins, L. Gu, A comparative study of RNN for outlier detection in data mining, in: Proceedings of the IEEE International Conference on Data Mining, IEEE, 2002, pp. 709-712.
-
(2002)
Proceedings of the IEEE International Conference on Data Mining
, pp. 709-712
-
-
Williams, G.1
Baxter, R.2
He, H.3
Hawkins, S.4
Gu, L.5
-
224
-
-
0036061014
-
Fault-diagnosis using neural networks with ellipsoidal basis functions
-
IEEE
-
S. Jakubek, T. Strasser, Fault-diagnosis using neural networks with ellipsoidal basis functions, in: Proceedings of the American Control Conference, vol. 5, IEEE, 2002, pp. 3846-3851.
-
(2002)
Proceedings of the American Control Conference
, vol.5
, pp. 3846-3851
-
-
Jakubek, S.1
Strasser, T.2
-
225
-
-
0036501528
-
Improving the performance of radial basis function classifiers in condition monitoring and fault diagnosis applications where 'unknown' faults may occur
-
DOI 10.1016/S0167-8655(01)00133-7, PII S0167865501001337
-
Y. Li, M. Pont, and N. Barrie Jones Improving the performance of radial basis function classifiers in condition monitoring and fault diagnosis applications where unknown faults may occur Pattern Recognit. Lett. 23 5 2002 569 577 (Pubitemid 34262287)
-
(2002)
Pattern Recognition Letters
, vol.23
, Issue.5
, pp. 569-577
-
-
Li, Y.1
Pont, M.J.2
Barrie Jones, N.3
-
226
-
-
35248885111
-
A self-organizing neural network for detecting novelties
-
DOI 10.1145/1244002.1244110, Proceedings of the 2007 ACM Symposium on Applied Computing
-
M.K. Albertini, R.F. de Mello, A self-organizing neural network for detecting novelties, in: Proceedings of the 2007 ACM Symposium on Applied Computing, SAC '07, ACM, New York, NY, USA, 2007, pp. 462-466. (Pubitemid 47568335)
-
(2007)
Proceedings of the ACM Symposium on Applied Computing
, pp. 462-466
-
-
Albertini, M.K.1
De Mello, R.F.2
-
227
-
-
69049086736
-
Time series clustering for anomaly detection using competitive neural networks
-
J. Príncipe, R. Miikkulainen, Springer, Berlin Heidelberg
-
G. Barreto, and L. Aguayo Time series clustering for anomaly detection using competitive neural networks J. Príncipe, R. Miikkulainen, Advances in Self-Organizing Maps, Lecture Notes in Computer Science vol. 5629 2009 Springer, Berlin Heidelberg 28 36
-
(2009)
Advances in Self-Organizing Maps, Lecture Notes in Computer Science
, vol.5629 VOL.
, pp. 28-36
-
-
Barreto, G.1
Aguayo, L.2
-
228
-
-
0037382210
-
On-line pattern analysis by evolving self-organizing maps
-
DOI 10.1016/S0925-2312(02)00599-4, PII S0925231202005994
-
D. Deng, and N. Kasabov On-line pattern analysis by evolving self-organizing maps Neurocomputing 51 2003 87 103 (Pubitemid 36367227)
-
(2003)
Neurocomputing
, vol.51
, pp. 87-103
-
-
Deng, D.1
Kasabov, N.2
-
229
-
-
84861761321
-
Autonomous growing neural gas for applications with time constraint optimal parameter estimation
-
J. García-Rodríguez, A. Angelopoulou, J. García-Chamizo, A. Psarrou, S. Orts Escolano, and V. Morell Giménez Autonomous growing neural gas for applications with time constraint optimal parameter estimation Neural Netw. 32 2012 196 208
-
(2012)
Neural Netw.
, vol.32
, pp. 196-208
-
-
García-Rodríguez, J.1
Angelopoulou, A.2
García-Chamizo, J.3
Psarrou, A.4
Orts Escolano, S.5
Morell Giménez, V.6
-
230
-
-
37249061630
-
Ligand-based virtual screening by novelty detection with self-organizing maps
-
DOI 10.1021/ci700040r
-
D. Hristozov, T. Oprea, and J. Gasteiger Ligand-based virtual screening by novelty detection with self-organizing maps J. Chem. Inf. Model. 47 6 2007 2044 2062 (Pubitemid 350275072)
-
(2007)
Journal of Chemical Information and Modeling
, vol.47
, Issue.6
, pp. 2044-2062
-
-
Hristozov, D.1
Oprea, T.I.2
Gasteiger, J.3
-
231
-
-
84455175284
-
Novelty detection using growing neural gas for visuo-spatial memory
-
D. Kit, B. Sullivan, D. Ballard, Novelty detection using growing neural gas for visuo-spatial memory, in: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, 2011, pp. 1194-1200.
-
(2011)
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE
, pp. 1194-1200
-
-
Kit, D.1
Sullivan, B.2
Ballard, D.3
-
232
-
-
0036789790
-
A self-organising network that grows when required
-
S. Marsland, J. Shapiro, and U. Nehmzow A self-organising network that grows when required Neural Netw. 15 8-9 2002 1041 1058
-
(2002)
Neural Netw.
, vol.15
, Issue.89
, pp. 1041-1058
-
-
Marsland, S.1
Shapiro, J.2
Nehmzow, U.3
-
233
-
-
16644365029
-
On-line novelty detection for autonomous mobile robots
-
DOI 10.1016/j.robot.2004.10.006, PII S0921889004002167
-
S. Marsland, U. Nehmzow, and J. Shapiro On-line novelty detection for autonomous mobile robots Robot. Auton. Syst. 51 2 2005 191 206 (Pubitemid 40480107)
-
(2005)
Robotics and Autonomous Systems
, vol.51
, Issue.2-3
, pp. 191-206
-
-
Marsland, S.1
Nehmzow, U.2
Shapiro, J.3
-
234
-
-
35248842651
-
Detecting anomalous network traffic with self-organizing maps
-
M. Ramadas, S. Ostermann, B. Tjaden, Detecting anomalous network traffic with self-organizing maps, in: Recent Advances in Intrusion Detection, Springer, 2003, pp. 36-54.
-
(2003)
Recent Advances in Intrusion Detection, Springer
, pp. 36-54
-
-
Ramadas, M.1
Ostermann, S.2
Tjaden, B.3
-
235
-
-
78049451757
-
An online adaptive condition-based maintenance method for mechanical systems
-
F. Wu, T. Wang, and J. Lee An online adaptive condition-based maintenance method for mechanical systems Mech. Syst. Signal Process. 24 8 2010 2985 2995
-
(2010)
Mech. Syst. Signal Process.
, vol.24
, Issue.8
, pp. 2985-2995
-
-
Wu, F.1
Wang, T.2
Lee, J.3
-
236
-
-
79952805765
-
Detection of anomalous insiders in collaborative environments via relational analysis of access logs
-
Y. Chen, B. Malin, Detection of anomalous insiders in collaborative environments via relational analysis of access logs, in: Proceedings of the 1st ACM Conference on Data and Application Security and Privacy, ACM, 2011, pp. 63-74.
-
(2011)
Proceedings of the 1st ACM Conference on Data and Application Security and Privacy, ACM
, pp. 63-74
-
-
Chen, Y.1
Malin, B.2
-
237
-
-
84863381941
-
Detecting anomalous insiders in collaborative information systems
-
Y. Chen, S. Nyemba, and B. Malin Detecting anomalous insiders in collaborative information systems IEEE Trans. Dependable Secur. Comput. 9 3 2012 332 344
-
(2012)
IEEE Trans. Dependable Secur. Comput.
, vol.9
, Issue.3
, pp. 332-344
-
-
Chen, Y.1
Nyemba, S.2
Malin, B.3
-
239
-
-
33750522220
-
Kernel PCA for novelty detection
-
DOI 10.1016/j.patcog.2006.07.009, PII S0031320306003414
-
H. Hoffmann Kernel PCA for novelty detection Pattern Recognit. 40 3 2007 863 874 (Pubitemid 44667761)
-
(2007)
Pattern Recognition
, vol.40
, Issue.3
, pp. 863-874
-
-
Hoffmann, H.1
-
240
-
-
33847290520
-
Mining anomalies using traffic feature distributions
-
DOI 10.1145/1090191.1080118
-
A. Lakhina, M. Crovella, and C. Diot Mining anomalies using traffic feature distributions ACM SIGCOMM Comput. Commun. Rev. 35 4 2005 217 228 (Pubitemid 46323506)
-
(2005)
Computer Communication Review
, vol.35
, Issue.4
, pp. 217-228
-
-
Lakhina, A.1
Crovella, M.2
Diot, C.3
-
241
-
-
59449095425
-
Incremental data-driven learning of a novelty detection model for one-class classification with application to high-dimensional noisy data
-
R. Kassab, and F. Alexandre Incremental data-driven learning of a novelty detection model for one-class classification with application to high-dimensional noisy data Mach. Learn. 74 2 2009 191 234
-
(2009)
Mach. Learn.
, vol.74
, Issue.2
, pp. 191-234
-
-
Kassab, R.1
Alexandre, F.2
-
242
-
-
79952320406
-
Feature extraction for novelty detection as applied to fault detection in machinery
-
J. McBain, and M. Timusk Feature extraction for novelty detection as applied to fault detection in machinery Pattern Recognit. Lett. 32 7 2011 1054 1061
-
(2011)
Pattern Recognit. Lett.
, vol.32
, Issue.7
, pp. 1054-1061
-
-
McBain, J.1
Timusk, M.2
-
243
-
-
33947132163
-
On-line novelty detection by recursive dynamic principal component analysis and gas sensor arrays under drift conditions
-
A. Perera, N. Papamichail, N. Bârsan, U. Weimar, and S. Marco On-line novelty detection by recursive dynamic principal component analysis and gas sensor arrays under drift conditions IEEE Sens. J. 6 3 2006 770 783
-
(2006)
IEEE Sens. J.
, vol.6
, Issue.3
, pp. 770-783
-
-
Perera, A.1
Papamichail, N.2
Bârsan, N.3
Weimar, U.4
Marco, S.5
-
245
-
-
84893306384
-
-
Technical Report, DTIC Document
-
M. Shyu, S. Chen, K. Sarinnapakorn, L. Chang, A Novel Anomaly Detection Scheme Based on Principal Component Classifier, Technical Report, DTIC Document, 2003.
-
(2003)
A Novel Anomaly Detection Scheme Based on Principal Component Classifier
-
-
Shyu, M.1
Chen, S.2
Sarinnapakorn, K.3
Chang, L.4
-
246
-
-
0043166339
-
Anomaly detection in IP networks
-
M. Thottan, and C. Ji Anomaly detection in IP networks IEEE Trans. Signal Process. 51 8 2003 2191 2204
-
(2003)
IEEE Trans. Signal Process.
, vol.51
, Issue.8
, pp. 2191-2204
-
-
Thottan, M.1
Ji, C.2
-
247
-
-
77953782136
-
Novelty detection in projected spaces for structural health monitoring
-
J. Toivola, M. Prada, and J. Hollmén Novelty detection in projected spaces for structural health monitoring Adv. Intell. Data Anal. IX 6065 2010 208 219
-
(2010)
Adv. Intell. Data Anal. IX
, vol.6065
, pp. 208-219
-
-
Toivola, J.1
Prada, M.2
Hollmén, J.3
-
248
-
-
84866013812
-
L1 norm based KPCA for novelty detection
-
Y. Xiao, H. Wang, W. Xu, and J. Zhou L1 norm based KPCA for novelty detection Pattern Recognit. 46 1 2013 389 396
-
(2013)
Pattern Recognit.
, vol.46
, Issue.1
, pp. 389-396
-
-
Xiao, Y.1
Wang, H.2
Xu, W.3
Zhou, J.4
-
249
-
-
40249093592
-
Evolving a dynamic predictive coding mechanism for novelty detection
-
S. Haggett, D. Chu, and I. Marshall Evolving a dynamic predictive coding mechanism for novelty detection Knowl. Based Syst. 21 3 2008 217 224
-
(2008)
Knowl. Based Syst.
, vol.21
, Issue.3
, pp. 217-224
-
-
Haggett, S.1
Chu, D.2
Marshall, I.3
-
250
-
-
21844470231
-
Dynamic predictive coding by the retina
-
DOI 10.1038/nature03689
-
T. Hosoya, S. Baccus, and M. Meister Dynamic predictive coding by the retina Nature 436 7047 2005 71 77 (Pubitemid 40966187)
-
(2005)
Nature
, vol.436
, Issue.7047
, pp. 71-77
-
-
Hosoya, T.1
Baccus, S.A.2
Meister, M.3
-
251
-
-
0025489075
-
The self-organizing map
-
T. Kohonen The self-organizing map Proc. IEEE 78 9 1990 1464 1480
-
(1990)
Proc. IEEE
, vol.78
, Issue.9
, pp. 1464-1480
-
-
Kohonen, T.1
-
252
-
-
0142095451
-
NSOM a real-time network-based intrusion detection system using self-organizing maps
-
K. Labib, and R. Vemuri NSOM a real-time network-based intrusion detection system using self-organizing maps Netw. Secur. 2002 1 6
-
(2002)
Netw. Secur.
, pp. 1-6
-
-
Labib, K.1
Vemuri, R.2
-
253
-
-
0034186912
-
Dynamic self-organizing maps with controlled growth for knowledge discovery
-
D. Alahakoon, S. Halgamuge, and B. Srinivasan Dynamic self-organizing maps with controlled growth for knowledge discovery IEEE Trans. Neural Netw. 11 3 2000 601 614
-
(2000)
IEEE Trans. Neural Netw.
, vol.11
, Issue.3
, pp. 601-614
-
-
Alahakoon, D.1
Halgamuge, S.2
Srinivasan, B.3
-
254
-
-
84943228749
-
Incremental grid growing: Encoding high-dimensional structure into a two-dimensional feature map
-
J. Blackmore, R. Miikkulainen, Incremental grid growing: encoding high-dimensional structure into a two-dimensional feature map, in: Proceedings of the IEEE International Conference on Neural Networks, vol. 1, 1993, pp. 450-455.
-
(1993)
Proceedings of the IEEE International Conference on Neural Networks
, vol.1
, pp. 450-455
-
-
Blackmore, J.1
Miikkulainen, R.2
-
255
-
-
0028748949
-
Growing cell structures - A self-organizing network for unsupervised and supervised learning
-
B. Fritzke Growing cell structures - a self-organizing network for unsupervised and supervised learning Neural Netw. 7 9 1994 1441 1460
-
(1994)
Neural Netw.
, vol.7
, Issue.9
, pp. 1441-1460
-
-
Fritzke, B.1
-
256
-
-
85135470835
-
A growing neural gas network learns topologies
-
B. Fritzke A growing neural gas network learns topologies Adv. Neural Inf. Process. Syst. 7 1995 625 632
-
(1995)
Adv. Neural Inf. Process. Syst.
, vol.7
, pp. 625-632
-
-
Fritzke, B.1
-
258
-
-
32344449062
-
An approach to spacecraft anomaly detection problem using Kernel Feature Space
-
DOI 10.1145/1081870.1081917, KDD-2005 - Proceedings of the 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
-
R. Fujimaki, T. Yairi, K. Machida, An approach to spacecraft anomaly detection problem using kernel feature space, in: Proceedings of the 11th ACM International Conference on Knowledge Discovery in Data Mining (SIGKDD), ACM, 2005, pp. 401-410. (Pubitemid 43218302)
-
(2005)
Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
, pp. 401-410
-
-
Fujimaki, R.1
Yairi, T.2
Machida, K.3
-
259
-
-
0347243182
-
Nonlinear Component Analysis as a Kernel Eigenvalue Problem
-
B. Schölkopf, A. Smola, and K. Müller Nonlinear component analysis as a kernel eigenvalue problem Neural Comput. 10 5 1998 1299 1319 (Pubitemid 128463674)
-
(1998)
Neural Computation
, vol.10
, Issue.5
, pp. 1299-1319
-
-
Scholkopf, B.1
Smola, A.2
Muller, K.-R.3
-
260
-
-
48049103479
-
Principal component analysis based on l1-norm maximization
-
N. Kwak Principal component analysis based on l1-norm maximization IEEE Trans. Pattern Anal. Mach. Intell. 30 9 2008 1672 1680
-
(2008)
IEEE Trans. Pattern Anal. Mach. Intell.
, vol.30
, Issue.9
, pp. 1672-1680
-
-
Kwak, N.1
-
261
-
-
12244268431
-
Graph-based anomaly detection
-
C. Noble, D. Cook, Graph-based anomaly detection, in: Proceedings of the 9th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), ACM, 2003, pp. 631-636.
-
(2003)
Proceedings of the 9th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), ACM
, pp. 631-636
-
-
Noble, C.1
Cook, D.2
-
262
-
-
34548580783
-
Neighborhood formation and anomaly detection in bipartite graphs
-
DOI 10.1109/ICDM.2005.103, 1565707, Proceedings - Fifth IEEE International Conference on Data Mining, ICDM 2005
-
J. Sun, H. Qu, D. Chakrabarti, C. Faloutsos, Neighborhood formation and anomaly detection in bipartite graphs, in: Proceedings of the 5th IEEE International Conference on Data Mining, IEEE, 2005, pp. 418-425. (Pubitemid 47385721)
-
(2005)
Proceedings - IEEE International Conference on Data Mining, ICDM
, pp. 418-425
-
-
Jimeng, S.1
Huiming, Q.2
Chakrabarti, D.3
Faloutsos, C.4
-
263
-
-
49749100928
-
Less is more: Compact matrix decomposition for large sparse graphs
-
J. Sun, Y. Xie, H. Zhang, C. Faloutsos, Less is more: compact matrix decomposition for large sparse graphs, in: Proceedings of the 7th SIAM International Conference in Data Mining, 2007.
-
(2007)
Proceedings of the 7th SIAM International Conference in Data Mining
-
-
Sun, J.1
Xie, Y.2
Zhang, H.3
Faloutsos, C.4
-
264
-
-
34547338342
-
Hierarchical anomaly detection in distributed large-scale sensor networks
-
V. Chatzigiannakis, S. Papavassiliou, M. Grammatikou, B. Maglaris, Hierarchical anomaly detection in distributed large-scale sensor networks, in: Proceedings of the 11th IEEE Symposium on Computers and Communications, ISCC'06, IEEE, 2006, pp. 761-767.
-
(2006)
Proceedings of the 11th IEEE Symposium on Computers and Communications, ISCC'06, IEEE
, pp. 761-767
-
-
Chatzigiannakis, V.1
Papavassiliou, S.2
Grammatikou, M.3
Maglaris, B.4
-
267
-
-
0033220728
-
Support vector domain description
-
DOI 10.1016/S0167-8655(99)00087-2
-
D. Tax, and R. Duin Support vector domain description Pattern Recognit. Lett. 20 11 1999 1191 1199 (Pubitemid 32261897)
-
(1999)
Pattern Recognition Letters
, vol.20
, Issue.11-13
, pp. 1191-1199
-
-
Tax, D.M.J.1
Duin, R.P.W.2
-
269
-
-
70349681015
-
Robust anomaly detection using support vector machines
-
W. Hu, Y. Liao, V. Vemuri, Robust anomaly detection using support vector machines, in: Proceedings of the International Conference on Machine Learning, 2003, pp. 282-289.
-
(2003)
Proceedings of the International Conference on Machine Learning
, pp. 282-289
-
-
Hu, W.1
Liao, Y.2
Vemuri, V.3
-
270
-
-
84863048595
-
A new online learning with kernels method in novelty detection
-
G. Li, C. Wen, Z. Li, A new online learning with kernels method in novelty detection, in: Proceedings of the 37th Annual Conference on IEEE Industrial Electronics Society (IECON), IEEE, 2011, pp. 2311-2316.
-
(2011)
Proceedings of the 37th Annual Conference on IEEE Industrial Electronics Society (IECON), IEEE
, pp. 2311-2316
-
-
Li, G.1
Wen, C.2
Li, Z.3
-
271
-
-
85096855936
-
One-class SVMs for document classification
-
L. Manevitz, and M. Yousef One-class SVMs for document classification J. Mach. Learn. Res. 2 2002 139 154
-
(2002)
J. Mach. Learn. Res.
, vol.2
, pp. 139-154
-
-
Manevitz, L.1
Yousef, M.2
-
272
-
-
84898950762
-
A linear programming approach to novelty detection
-
The MIT Press
-
C. Campbell, K. Bennett, A linear programming approach to novelty detection, in: Proceedings of the Conference on Advances in Neural Information Processing Systems, vol. 13, The MIT Press, 2001, pp. 395-401.
-
(2001)
Proceedings of the Conference on Advances in Neural Information Processing Systems
, vol.13
, pp. 395-401
-
-
Campbell, C.1
Bennett, K.2
-
273
-
-
79959415640
-
An optimal sphere and two large margins approach for novelty detection
-
T. Le, D. Tran, W. Ma, D. Sharma, An optimal sphere and two large margins approach for novelty detection, in: Proceedings of the International Joint Conference on Neural Networks (IJCNN), IEEE, 2010, pp. 1-6.
-
(2010)
Proceedings of the International Joint Conference on Neural Networks (IJCNN), IEEE
, pp. 1-6
-
-
Le, T.1
Tran, D.2
Ma, W.3
Sharma, D.4
-
274
-
-
79957956807
-
Multiple distribution data description learning algorithm for novelty detection
-
T. Le, D. Tran, W. Ma, and D. Sharma Multiple distribution data description learning algorithm for novelty detection Adv. Knowl. Discov. Data Min. 6635 2011 246 257
-
(2011)
Adv. Knowl. Discov. Data Min.
, vol.6635
, pp. 246-257
-
-
Le, T.1
Tran, D.2
Ma, W.3
Sharma, D.4
-
275
-
-
77955514045
-
Fast support vector data descriptions for novelty detection
-
Y.-H. Liu, Y.-C. Liu, and Y.-J. Chen Fast support vector data descriptions for novelty detection IEEE Trans. Neural Netw. 21 8 2010 1296 1313
-
(2010)
IEEE Trans. Neural Netw.
, vol.21
, Issue.8
, pp. 1296-1313
-
-
Liu, Y.-H.1
Liu, Y.-C.2
Chen, Y.-J.3
-
276
-
-
79151475707
-
High-speed inline defect detection for TFT-LCD array process using a novel support vector data description
-
Y.-H. Liu, Y.-C. Liu, and Y.-Z. Chen High-speed inline defect detection for TFT-LCD array process using a novel support vector data description Exp. Syst. Appl. 38 5 2011 6222 6231
-
(2011)
Exp. Syst. Appl.
, vol.38
, Issue.5
, pp. 6222-6231
-
-
Liu, Y.-H.1
Liu, Y.-C.2
Chen, Y.-Z.3
-
277
-
-
84867736801
-
Efficient support vector data descriptions for novelty detection
-
X. Peng, and D. Xu Efficient support vector data descriptions for novelty detection Neural Comput. Appl. 21 8 2012 2023 2032
-
(2012)
Neural Comput. Appl.
, vol.21
, Issue.8
, pp. 2023-2032
-
-
Peng, X.1
Xu, D.2
-
278
-
-
70349915779
-
A small sphere and large margin approach for novelty detection using training data with outliers
-
M. Wu, and J. Ye A small sphere and large margin approach for novelty detection using training data with outliers IEEE Trans. Pattern Anal. Mach. Intell. 31 11 2009 2088 2092
-
(2009)
IEEE Trans. Pattern Anal. Mach. Intell.
, vol.31
, Issue.11
, pp. 2088-2092
-
-
Wu, M.1
Ye, J.2
-
279
-
-
77951198697
-
Multi-sphere support vector data description for outliers detection on multi-distribution data
-
Y. Xiao, B. Liu, L. Cao, X. Wu, C. Zhang, Z. Hao, F. Yang, J. Cao, Multi-sphere support vector data description for outliers detection on multi-distribution data, in: Proceedings of the IEEE International Conference on Data Mining Workshops (ICDMW), IEEE, 2009, pp. 82-87.
-
(2009)
Proceedings of the IEEE International Conference on Data Mining Workshops (ICDMW), IEEE
, pp. 82-87
-
-
Xiao, Y.1
Liu, B.2
Cao, L.3
Wu, X.4
Zhang, C.5
Hao, Z.6
Yang, F.7
Cao, J.8
-
280
-
-
33745917684
-
Support vector machine in novelty detection for multi-channel combustion data
-
DOI 10.1007/11760191-122, Advances in Neural Networks - ISNN 2006: Third International Symposium on Neural Networks, ISNN 2006, Proceedings - Part III
-
L. Clifton, H. Yin, and Y. Zhang Support vector machine in novelty detection for multi-channel combustion data Adv. Neural Netw. (ISNN) 3973 2006 836 843 (Pubitemid 44045793)
-
(2006)
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
, vol.3973
, pp. 836-843
-
-
Clifton, L.A.1
Yin, H.2
Zhang, Y.3
-
281
-
-
34748909393
-
Combined support vector novelty detection for multi-channel combustion data
-
DOI 10.1109/ICNSC.2007.372828, 4239041, 2007 IEEE International Conference on Networking, Sensing and Control, ICNSC'07
-
L. Clifton, H. Yin, D. Clifton, Y. Zhang, Combined support vector novelty detection for multi-channel combustion data, in: Proceedings of the IEEE International Conference on Networking, Sensing and Control, IEEE, 2007, pp. 495-500. (Pubitemid 47468840)
-
(2007)
2007 IEEE International Conference on Networking, Sensing and Control, ICNSC'07
, pp. 495-500
-
-
Clifton, L.A.1
Yin, H.2
Clifton, D.A.3
Zhang, Y.4
-
282
-
-
33845454236
-
Taming the curse of dimensionality in kernels and novelty detection
-
P.F. Evangelista, M.J. Embrechts, B.K. Szymanski, Taming the curse of dimensionality in kernels and novelty detection, in: Applied Soft Computing Technologies: The Challenge of Complexity, Springer Verlag, 2006, pp. 431-444.
-
(2006)
Applied Soft Computing Technologies: The Challenge of Complexity, Springer Verlag
, pp. 431-444
-
-
Evangelista, P.F.1
Embrechts, M.J.2
Szymanski, B.K.3
-
284
-
-
33745915605
-
FMRI analysis via one-class machine learning techniques
-
Morgan Kaufmann Publishers Inc., San Francisco, CA, USA
-
D.R. Hardoon, L.M. Manevitz, fMRI analysis via one-class machine learning techniques, in: Proceedings of the 19th International Joint Conference on Artificial intelligence, IJCAI'05, Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 2005, pp. 1604-1605.
-
(2005)
Proceedings of the 19th International Joint Conference on Artificial Intelligence, IJCAI'05
, pp. 1604-1605
-
-
Hardoon, D.R.1
Manevitz, L.M.2
-
285
-
-
33846981146
-
Static and dynamic novelty detection methods for jet engine health monitoring
-
P. Hayton, S. Utete, D. King, S. King, P. Anuzis, and L. Tarassenko Static and dynamic novelty detection methods for jet engine health monitoring Philos. Trans. R. Soc. A Math. Phys. Eng. Sci. 365 1851 2007 493 514
-
(2007)
Philos. Trans. R. Soc. A Math. Phys. Eng. Sci.
, vol.365
, Issue.1851
, pp. 493-514
-
-
Hayton, P.1
Utete, S.2
King, D.3
King, S.4
Anuzis, P.5
Tarassenko, L.6
-
286
-
-
33646512999
-
One class support vector machines for detecting anomalous windows registry accesses
-
K. Heller, K. Svore, A. Keromytis, S. Stolfo, One class support vector machines for detecting anomalous windows registry accesses, in: Proceedings of the Workshop on Data Mining for Computer Security, 2003.
-
(2003)
Proceedings of the Workshop on Data Mining for Computer Security
-
-
Heller, K.1
Svore, K.2
Keromytis, A.3
Stolfo, S.4
-
287
-
-
32344452166
-
A comparative study of anomaly detection schemes in network intrusion detection
-
SIAM
-
A. Lazarevic, L. Ertoz, V. Kumar, A. Ozgur, J. Srivastava, A comparative study of anomaly detection schemes in network intrusion detection, in: Proceedings of the 3rd SIAM International Conference on Data Mining, vol. 3, SIAM, 2003, pp. 25-36.
-
(2003)
Proceedings of the 3rd SIAM International Conference on Data Mining
, vol.3
, pp. 25-36
-
-
Lazarevic, A.1
Ertoz, L.2
Kumar, V.3
Ozgur, A.4
Srivastava, J.5
-
288
-
-
33745815656
-
Application of LVQ to novelty detection using outlier training data
-
DOI 10.1016/j.patrec.2006.02.019, PII S0167865506000754
-
H. Lee, and S. Cho Application of LVQ to novelty detection using outlier training data Pattern Recognit. Lett. 27 13 2006 1572 1579 (Pubitemid 44037113)
-
(2006)
Pattern Recognition Letters
, vol.27
, Issue.13
, pp. 1572-1579
-
-
Lee, H.-j.1
Cho, S.2
-
289
-
-
70350649248
-
Online novelty detection on temporal sequences
-
J. Ma, S. Perkins, Online novelty detection on temporal sequences, in: Proceedings of the Ninth ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), ACM, 2003, pp. 613-618.
-
(2003)
Proceedings of the Ninth ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), ACM
, pp. 613-618
-
-
Ma, J.1
Perkins, S.2
-
290
-
-
0141682928
-
Time-series novelty detection using one-class support vector machines
-
IEEE
-
J. Ma, S. Perkins, Time-series novelty detection using one-class support vector machines, in: Proceedings of the International Joint Conference on Neural Networks, vol. 3, IEEE, 2003, pp. 1741-1745.
-
(2003)
Proceedings of the International Joint Conference on Neural Networks
, vol.3
, pp. 1741-1745
-
-
Ma, J.1
Perkins, S.2
-
291
-
-
58049169022
-
New approaches based on one-class SVMs for impulsive sounds recognition tasks
-
A. Rabaoui, H. Kadri, N. Ellouze, New approaches based on one-class SVMs for impulsive sounds recognition tasks, in: Proceedings of the IEEE Workshop on Machine Learning for Signal Processing, IEEE, 2008, pp. 285-290.
-
(2008)
Proceedings of the IEEE Workshop on Machine Learning for Signal Processing, IEEE
, pp. 285-290
-
-
Rabaoui, A.1
Kadri, H.2
Ellouze, N.3
-
292
-
-
57649150671
-
Parameter optimization of kernel-based one-class classifier on imbalance learning
-
L. Zhuang, and H. Dai Parameter optimization of kernel-based one-class classifier on imbalance learning J. Comput. 1 7 2006 32 40
-
(2006)
J. Comput.
, vol.1
, Issue.7
, pp. 32-40
-
-
Zhuang, L.1
Dai, H.2
-
293
-
-
34249317907
-
Fuzzy c-means clustering algorithm based on kernel method
-
Z. Wu, W. Xie, J. Yu, Fuzzy c-means clustering algorithm based on kernel method, in: Proceedings of the 5th International Conference on Computational Intelligence and Multimedia Applications (ICCIMA), IEEE, 2003, pp. 49-54.
-
(2003)
Proceedings of the 5th International Conference on Computational Intelligence and Multimedia Applications (ICCIMA), IEEE
, pp. 49-54
-
-
Wu, Z.1
Xie, W.2
Yu, J.3
-
295
-
-
33645717587
-
Kernel fisher discriminants for outlier detection
-
DOI 10.1162/089976606775774679
-
V. Roth Kernel fisher discriminants for outlier detection Neural Comput. 18 4 2006 942 960 (Pubitemid 43543827)
-
(2006)
Neural Computation
, vol.18
, Issue.4
, pp. 942-960
-
-
Roth, V.1
-
296
-
-
77953098563
-
Anomaly detection through a Bayesian support vector machine
-
V. Sotiris, P. Tse, and M. Pecht Anomaly detection through a Bayesian support vector machine IEEE Trans. Reliab. 59 2 2010 277 286
-
(2010)
IEEE Trans. Reliab.
, vol.59
, Issue.2
, pp. 277-286
-
-
Sotiris, V.1
Tse, P.2
Pecht, M.3
-
299
-
-
27144543595
-
An optimization model for outlier detection in categorical data
-
Advances in Intelligent Computing: International Conference on Intelligent Computing, ICIC 2005. Proceedings
-
Z. He, S. Deng, and X. Xu An optimization model for outlier detection in categorical data Adv. Intell. Comput. 3644 2005 400 409 (Pubitemid 41491080)
-
(2005)
Lecture Notes in Computer Science
, vol.3644
, Issue.PART I
, pp. 400-409
-
-
He, Z.1
Deng, S.2
Xu, X.3
-
300
-
-
33745779262
-
A fast greedy algorithm for outlier mining
-
DOI 10.1007/11731139-67, Advances in Knowledge Discovery and Data Mining - 10th Pacific-Asia Conference, PAKDD 2006, Proceedings
-
Z. He, S. Deng, X. Xu, and J. Huang A fast greedy algorithm for outlier mining Adv. Knowl. Discov. Data Min. 3918 2006 567 576 (Pubitemid 44019460)
-
(2006)
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
, vol.3918
, pp. 567-576
-
-
He, Z.1
Deng, S.2
Xu, X.3
Huang, J.Z.4
-
301
-
-
49749087938
-
Clustering needles in a haystack: An information theoretic analysis of minority and outlier detection
-
S. Ando, Clustering needles in a haystack: an information theoretic analysis of minority and outlier detection, in: Proceedings of the 7th IEEE International Conference on Data Mining, ICDM'07, IEEE, 2007, pp. 13-22.
-
(2007)
Proceedings of the 7th IEEE International Conference on Data Mining, ICDM'07, IEEE
, pp. 13-22
-
-
Ando, S.1
-
302
-
-
10644281769
-
Towards parameter-free data mining
-
KDD-2004 - Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
-
E. Keogh, S. Lonardi, C. Ratanamahatana, Towards parameter-free data mining, in: Proceedings of the 10th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), ACM, 2004, pp. 206-215. (Pubitemid 40114930)
-
(2004)
KDD-2004 - Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
, pp. 206-215
-
-
Keogh, E.1
Lonardi, S.2
Ratanamahatana, C.A.3
-
303
-
-
33845271242
-
Finding the most unusual time series subsequence: Algorithms and applications
-
DOI 10.1007/s10115-006-0034-6
-
E. Keogh, J. Lin, S. Lee, and H. Herle Finding the most unusual time series subsequence algorithms and applications Knowl. Inf. Syst. 11 1 2007 1 27 (Pubitemid 44857541)
-
(2007)
Knowledge and Information Systems
, vol.11
, Issue.1
, pp. 1-27
-
-
Keogh, E.1
Lin, J.2
Lee, S.-H.3
Van Herle, H.4
-
304
-
-
27544465147
-
Approximations to magic: Finding unusual medical time series
-
Proceedings - 18th IEEE Symposium on Computer-Based Medical Systems
-
J. Lin, E. Keogh, A. Fu, H. Van Herle, Approximations to magic: finding unusual medical time series, in: Proceedings of the 18th IEEE Symposium on Computer-Based Medical Systems, IEEE, 2005, pp. 329-334. (Pubitemid 41542915)
-
(2005)
Proceedings - IEEE Symposium on Computer-Based Medical Systems
, pp. 329-334
-
-
Lin, J.1
Keogh, E.2
Fu, A.3
Van Herle, H.4
-
305
-
-
33749406603
-
Finding time series discords based on haar transform
-
Advanced Data Mining and Applications - Second International Conference, ADMA 2006, Proceedings
-
A. Fu, O. Leung, E. Keogh, and J. Lin Finding time series discords based on haar transform Adv. Data Min. Appl. 4093 2006 31 41 (Pubitemid 44503140)
-
(2006)
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
, vol.4093
, pp. 31-41
-
-
Fu, A.W.-C.1
Leung, O.T.-W.2
Keogh, E.3
Lin, J.4
-
306
-
-
85081787178
-
Graph-based text representation for novelty detection
-
Stroudsburg, PA, USA
-
M. Gamon, Graph-based text representation for novelty detection, in: Proceedings of the First Workshop on Graph Based Methods for Natural Language Processing, Association for Computational Linguistics, Stroudsburg, PA, USA, 2006, pp. 17-24.
-
(2006)
Proceedings of the First Workshop on Graph Based Methods for Natural Language Processing, Association for Computational Linguistics
, pp. 17-24
-
-
Gamon, M.1
-
307
-
-
70449717021
-
Information theoretic novelty detection
-
M. Filippone, and G. Sanguinetti Information theoretic novelty detection Pattern Recognit. 43 3 2010 805 814
-
(2010)
Pattern Recognit.
, vol.43
, Issue.3
, pp. 805-814
-
-
Filippone, M.1
Sanguinetti, G.2
-
308
-
-
79951607505
-
A perturbative approach to novelty detection in autoregressive models
-
M. Filippone, and G. Sanguinetti A perturbative approach to novelty detection in autoregressive models IEEE Trans. Signal Process. 59 3 2011 1027 1036
-
(2011)
IEEE Trans. Signal Process.
, vol.59
, Issue.3
, pp. 1027-1036
-
-
Filippone, M.1
Sanguinetti, G.2
-
309
-
-
84893289952
-
-
Technical Report CS-09-06, Department of Computer Science, University of Sheffield
-
M. Filippone, G. Sanguinetti, Novelty Detection in Autoregressive Models Using Information Theoretic Measures, Technical Report CS-09-06, Department of Computer Science, University of Sheffield, 2009.
-
(2009)
Novelty Detection in Autoregressive Models Using Information Theoretic Measures
-
-
Filippone, M.1
Sanguinetti, G.2
-
310
-
-
67349174184
-
Bayesian surprise attracts human attention
-
L. Itti, and P. Baldi Bayesian surprise attracts human attention Vis. Res. 49 10 2009 1295 1306
-
(2009)
Vis. Res.
, vol.49
, Issue.10
, pp. 1295-1306
-
-
Itti, L.1
Baldi, P.2
|