-
1
-
-
27144452309
-
A comparative study of rnn for outlier detection in data mining
-
G. J. Williams, R. A. Baxter, H. He, S. Hawkins, and L. Gu, "A comparative study of rnn for outlier detection in data mining", in ICDM, 2002, pp. 709-712.
-
(2002)
ICDM
, pp. 709-712
-
-
Williams, G.J.1
Baxter, R.A.2
He, H.3
Hawkins, S.4
Gu, L.5
-
5
-
-
84866676153
-
Automatic mitral leaflet tracking in echocardiography by outlier detection in the low-rank representation
-
X. Zhou, C. Yang, and W. Yu, "Automatic mitral leaflet tracking in echocardiography by outlier detection in the low-rank representation", in CVPR, 2012, pp. 972-979.
-
(2012)
CVPR
, pp. 972-979
-
-
Zhou, X.1
Yang, C.2
Yu, W.3
-
6
-
-
77952380096
-
Mining distance-based outliers in near linear time with randomization and a simple pruning rule
-
S. D. Bay and M. Schwabacher, "Mining distance-based outliers in near linear time with randomization and a simple pruning rule", in KDD, 2003, pp. 29-38.
-
(2003)
KDD
, pp. 29-38
-
-
Bay, S.D.1
Schwabacher, M.2
-
7
-
-
84864859588
-
Outlier detection using replicator neural networks
-
S. Hawkins, H. He, G. J. Williams, and R. A. Baxter, "Outlier detection using replicator neural networks", in DaWaK, 2002, pp. 170-180.
-
(2002)
DaWaK
, pp. 170-180
-
-
Hawkins, S.1
He, H.2
Williams, G.J.3
Baxter, R.A.4
-
8
-
-
0035788909
-
Mining top-n local outliers in large databases
-
W. Jin, A. K. H. Tung, and J. Han, "Mining top-n local outliers in large databases", in KDD, 2001, pp. 293-298.
-
(2001)
KDD
, pp. 293-298
-
-
Jin, W.1
Tung, A.K.H.2
Han, J.3
-
9
-
-
84862955840
-
Maximum margin/volume outlier detection
-
S. Li and I. W. Tsang, "Maximum margin/volume outlier detection", in ICTAI, 2011, pp. 385-392.
-
(2011)
ICTAI
, pp. 385-392
-
-
Li, S.1
Tsang, I.W.2
-
10
-
-
0034592785
-
Using the fractal dimension to cluster datasets
-
D. Barbará and P. Chen, "Using the fractal dimension to cluster datasets", in KDD, 2000, pp. 260-264.
-
(2000)
KDD
, pp. 260-264
-
-
Barbará, D.1
Chen, P.2
-
11
-
-
58149109880
-
Efficient clusteringbased outlier detection algorithm for dynamic data stream
-
M. Elahi, K. Li, W. Nisar, X. Lv, and H. Wang, "Efficient clusteringbased outlier detection algorithm for dynamic data stream", in FSKD (5), 2008, pp. 298-304.
-
(2008)
FSKD (5)
, pp. 298-304
-
-
Elahi, M.1
Li, K.2
Nisar, W.3
Lv, X.4
Wang, H.5
-
12
-
-
77649275031
-
A fast outlier detection strategy for distributed high-dimensional data sets with mixed attributes
-
A. Koufakou and M. Georgiopoulos, "A fast outlier detection strategy for distributed high-dimensional data sets with mixed attributes", Data Min. Knowl. Discov., vol. 20, no. 2, pp. 259-289, 2010.
-
(2010)
Data Min. Knowl. Discov.
, vol.20
, Issue.2
, pp. 259-289
-
-
Koufakou, A.1
Georgiopoulos, M.2
-
13
-
-
0035788943
-
Detecting graph-based spatial outliers: Algorithms and applications (a summary of results)
-
S. Shekhar, C. T. Lu, and P. Zhang, "Detecting graph-based spatial outliers: algorithms and applications (a summary of results)", in KDD, 2001, pp. 371-376.
-
(2001)
KDD
, pp. 371-376
-
-
Shekhar, S.1
Lu, C.T.2
Zhang, P.3
-
14
-
-
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, and J. Cao, "Multi-sphere support vector data description for outliers detection on multi-distribution data", in ICDM Workshops, 2009, pp. 82-87.
-
(2009)
ICDM Workshops
, 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
-
15
-
-
78650198205
-
A theoretical framework for multi-sphere support vector data description
-
T. Le, D. Tran, W. Ma, and D. Sharma, "A theoretical framework for multi-sphere support vector data description", in ICONIP (2), 2010, pp. 132-142.
-
(2010)
ICONIP (2)
, pp. 132-142
-
-
Le, T.1
Tran, D.2
Ma, W.3
Sharma, D.4
-
16
-
-
84878584659
-
Proximity multisphere support vector clustering
-
T. Le, D. Tran, P. Nguyen, W. Ma, and D. Sharma, "Proximity multisphere support vector clustering", Neural Computing and Applications, vol. 22, no. 7-8, pp. 1309-1319, 2013.
-
(2013)
Neural Computing and Applications
, vol.22
, Issue.7-8
, pp. 1309-1319
-
-
Le, T.1
Tran, D.2
Nguyen, P.3
Ma, W.4
Sharma, D.5
-
17
-
-
0000487102
-
Estimating the support of a high-dimensional distribution
-
B. Schölkopf, J. C. Platt, J. Shawe-Taylor, A. J. Smola, and R. C. Williamson, "Estimating the support of a high-dimensional distribution", Neural Computation, vol. 13, no. 7, pp. 1443-1471, 2001.
-
(2001)
Neural Computation
, vol.13
, Issue.7
, pp. 1443-1471
-
-
Schölkopf, B.1
Platt, J.C.2
Shawe-Taylor, J.3
Smola, A.J.4
Williamson, R.C.5
-
18
-
-
33646512999
-
One class support vector machines for detecting anomalous windows registry accesses
-
K. A. Heller, K. M. Svore, A. D. Keromytis, and S. J. Stolfo, "One class support vector machines for detecting anomalous windows registry accesses", in The Workshop on Data Mining for Computer Security, 2003.
-
(2003)
The Workshop on Data Mining for Computer Security
-
-
Heller, K.A.1
Svore, K.M.2
Keromytis, A.D.3
Stolfo, S.J.4
-
19
-
-
70449559229
-
Using one-class svm outliers detection for verification of collaboratively tagged image training sets
-
H. M. Lukashevich, S. Nowak, and P. Dunker, "Using one-class svm outliers detection for verification of collaboratively tagged image training sets", in IEEE International Conference on Multimedia and Expo (ICME), 2009, pp. 682-685.
-
(2009)
IEEE International Conference on Multimedia and Expo (ICME)
, pp. 682-685
-
-
Lukashevich, H.M.1
Nowak, S.2
Dunker, P.3
-
20
-
-
80052246992
-
One class classification for anomaly detection: Support vector data description revisited
-
E. J. Pauwels and O. Ambekar, "One class classification for anomaly detection: Support vector data description revisited", in ICDM, 2011, pp. 25-39.
-
(2011)
ICDM
, pp. 25-39
-
-
Pauwels, E.J.1
Ambekar, O.2
-
22
-
-
77955690054
-
The augmented lagrange multiplier method for exact recovery of corrupted low-rank matrices
-
Z. C. Lin, M. M. Chen, L. Q. Wu, and Y. Ma, "The augmented lagrange multiplier method for exact recovery of corrupted low-rank matrices", Technique Report, UIUC, 2009.
-
(2009)
Technique Report, UIUC
-
-
Lin, Z.C.1
Chen, M.M.2
Wu, L.Q.3
Ma, Y.4
-
23
-
-
84896061548
-
Low-rank coding with b-matching constraint for semi-supervised classification
-
S. Li and Y. Fu, "Low-rank coding with b-matching constraint for semi-supervised classification", in IJCAI, 2013, pp. 1472-1478.
-
(2013)
IJCAI
, pp. 1472-1478
-
-
Li, S.1
Fu, Y.2
-
24
-
-
84881505349
-
Discriminative dictionary learning with lowrank regularization for face recognition
-
L. Li, S. Li, and Y. Fu, "Discriminative dictionary learning with lowrank regularization for face recognition", in FG, 2013, pp. 1-6.
-
(2013)
FG
, pp. 1-6
-
-
Li, L.1
Li, S.2
Fu, Y.3
-
25
-
-
77951291046
-
A singular value thresholding algorithm for matrix completion
-
J. F. Cai, E. J. Candes, and Z. W. Shen, "A singular value thresholding algorithm for matrix completion", SIAM Journal on Optimization, vol. 20, no. 4, pp. 1956-1982, 2010.
-
(2010)
SIAM Journal on Optimization
, vol.20
, Issue.4
, pp. 1956-1982
-
-
Cai, J.F.1
Candes, E.J.2
Shen, Z.W.3
-
26
-
-
31844453456
-
Clustering through ranking on manifolds
-
M. Breitenbach and G. Z. Grudic, "Clustering through ranking on manifolds", in ICML, 2005, pp. 73-80.
-
(2005)
ICML
, pp. 73-80
-
-
Breitenbach, M.1
Grudic, G.Z.2
-
27
-
-
77957920407
-
Directional binary code with application to polyu near-infrared face database
-
B. Zhang, L. Zhang, D. Zhang, and L. Shen, "Directional binary code with application to polyu near-infrared face database", Pattern Recognition Letters, vol. 31, no. 14, pp. 2337-2344, 2010.
-
(2010)
Pattern Recognition Letters
, vol.31
, Issue.14
, pp. 2337-2344
-
-
Zhang, B.1
Zhang, L.2
Zhang, D.3
Shen, L.4
-
28
-
-
0347380229
-
The cmu pose, illumination, and expression database
-
T. Sim, S. Baker, and M. Bsat, "The cmu pose, illumination, and expression database", IEEE Trans. Pattern Anal. Mach. Intell., vol. 25, no. 12, pp. 1615-1618, 2003.
-
(2003)
IEEE Trans. Pattern Anal. Mach. Intell.
, vol.25
, Issue.12
, pp. 1615-1618
-
-
Sim, T.1
Baker, S.2
Bsat, M.3
|