-
1
-
-
0032089922
-
Approximating MAPs for belief networks is NP-hard and other theorems
-
PII S0004370298000435
-
A.M. Abdelbar, and S.M. Hedetniemi Approximating MAP for belief networks is NP-hard and other theorems Artificial Intelligence 102 1 1998 21 38 (Pubitemid 128378356)
-
(1998)
Artificial Intelligence
, vol.102
, Issue.1
, pp. 21-38
-
-
Abdelbar, A.M.1
Hedetniemi, S.M.2
-
3
-
-
26044441615
-
Feature selection in Bayesian classifiers for the prognosis of survival of cirrhotic patients treated with TIPS
-
DOI 10.1016/j.jbi.2005.05.004, PII S153204640500047X
-
R. Blanco, I. Inza, M. Merino, J. Quiroga, and P. Larrañaga Feature selection in Bayesian classifiers for the prognosis of survival of cirrhotic patients treated with TIPS Journal of Biomedical Informatics 38 5 2005 376 388 (Pubitemid 41405808)
-
(2005)
Journal of Biomedical Informatics
, vol.38
, Issue.5
, pp. 376-388
-
-
Blanco, R.1
Inza, I.2
Merino, M.3
Quiroga, J.4
Larranaga, P.5
-
4
-
-
3042597440
-
Learning multi-label scene classification
-
DOI 10.1016/j.patcog.2004.03.009, PII S0031320304001074
-
M.R. Boutell, J. Luo, X. Shen, and C.M. Brown Learning multi-label scene classification Pattern Recognition 37 9 2004 1757 1771 (Pubitemid 38804465)
-
(2004)
Pattern Recognition
, vol.37
, Issue.9
, pp. 1757-1771
-
-
Boutell, M.R.1
Luo, J.2
Shen, X.3
Brown, C.M.4
-
5
-
-
68949141664
-
Combining instance-based learning and logistic regression for multilabel classification
-
W. Cheng, and E. Hüllermeier Combining instance-based learning and logistic regression for multilabel classification Machine Learning 76 2-3 2009 211 225
-
(2009)
Machine Learning
, vol.76
, Issue.23
, pp. 211-225
-
-
Cheng, W.1
Hüllermeier, E.2
-
6
-
-
79955565563
-
A simple instance-based approach to multi-label classification using the Mallows model
-
W. Cheng, E. Hüllermeier, A simple instance-based approach to multi-label classification using the Mallows model, in: Proceedings of the Workshop on Learning from Multi-Label Data (MLD'09), 2009, pp. 28-38.
-
(2009)
Proceedings of the Workshop on Learning from Multi-Label Data (MLD'09)
, pp. 28-38
-
-
Cheng, W.1
-
7
-
-
35748943218
-
A discretization algorithm based on class-attribute contingency coefficient
-
T. Cheng-Jung, L. Chien-I, and Y. Wei-Pang A discretization algorithm based on class-attribute contingency coefficient Information Sciences 178 2008 714 731
-
(2008)
Information Sciences
, vol.178
, pp. 714-731
-
-
Cheng-Jung, T.1
Chien-I, L.2
Wei-Pang, Y.3
-
8
-
-
84933530882
-
Approximating discrete probability distributions with dependence trees
-
C. Chow, and C. Liu Approximating discrete probability distributions with dependence trees IEEE Transactions on Information Theory 14 1968 462 467
-
(1968)
IEEE Transactions on Information Theory
, vol.14
, pp. 462-467
-
-
Chow, C.1
Liu, C.2
-
9
-
-
0000666661
-
On the shortest arborescence of a directed graph
-
C. Chu, and T. Liu On the shortest arborescence of a directed graph Science Sinica 14 1968 1396 1400
-
(1968)
Science Sinica
, vol.14
, pp. 1396-1400
-
-
Chu, C.1
Liu, T.2
-
10
-
-
34249832377
-
A Bayesian method for the induction of probabilistic networks from data
-
G.F. Cooper, and E.A. Herskovits A Bayesian method for the induction of probabilistic networks from data Machine Learning 9 1992 309 347
-
(1992)
Machine Learning
, vol.9
, pp. 309-347
-
-
Cooper, G.F.1
Herskovits, E.A.2
-
12
-
-
31844433245
-
Learning as search optimization: Approximate large margin methods for structured prediction
-
H. Daumé III, D. Marcu, Learning as search optimization: approximate large margin methods for structured prediction, in: Proceedings of the International Conference on Machine Learning, 2005, pp. 169-176.
-
(2005)
Proceedings of the International Conference on Machine Learning
, pp. 169-176
-
-
Daumé Iii, H.1
-
13
-
-
0003064380
-
Applications of a general propagation algorithm for probabilistic expert systems
-
A.P. Dawid Applications of a general propagation algorithm for probabilistic expert systems Statistics and Computing 2 1992 25 36
-
(1992)
Statistics and Computing
, vol.2
, pp. 25-36
-
-
Dawid, A.P.1
-
14
-
-
67949108237
-
A tutorial on multi-label classification techniques
-
Springer, Foundations of Computational Intelligence
-
A. de Carvalho, and A.A. Freitas A tutorial on multi-label classification techniques Foundations of Computational Intelligence Studies in Computational Intelligence vol. 5 2009 Springer 177 195
-
(2009)
Studies in Computational Intelligence
, vol.5
, pp. 177-195
-
-
De Carvalho, A.1
Freitas, A.A.2
-
15
-
-
38049160416
-
Inference and learning in multi-dimensional Bayesian network classifiers
-
Springer, European Conference on Symbolic and Quantitative Approaches to Reasoning under Uncertainty
-
P.R. de Waal, and L.C. van der Gaag Inference and learning in multi-dimensional Bayesian network classifiers European Conference on Symbolic and Quantitative Approaches to Reasoning under Uncertainty Lecture Notes in Artificial Intelligence vol. 4724 2007 Springer 501 511
-
(2007)
Lecture Notes in Artificial Intelligence
, vol.4724
, pp. 501-511
-
-
De Waal, P.R.1
Van Der Gaag, L.C.2
-
16
-
-
84947926042
-
A fast elitist non-dominated sorting genetic algorithm for multi-objective optimisation: NSGA-II
-
K. Deb, S. Agrawal, A. Pratap, T. Meyarivan, A fast elitist non-dominated sorting genetic algorithm for multi-objective optimisation: NSGA-II, in: Parallel Problem Solving from Nature (PPSN VI), Lecture Notes in Computer Science, 1917, 2000, pp. 849-858.
-
(1917)
Parallel Problem Solving from Nature (PPSN VI), Lecture Notes in Computer Science
, pp. 849-858
-
-
Deb, K.1
Agrawal, S.2
Pratap, A.3
Meyarivan, T.4
-
17
-
-
0033188982
-
Bucket elimination: A unifying framework for reasoning
-
DOI 10.1016/S0004-3702(99)00059-4
-
R. Dechter Bucket elimination: a unifying framework for reasoning Artificial Intelligence 113 1-2 1999 41 85 (Pubitemid 30542742)
-
(1999)
Artificial Intelligence
, vol.113
, Issue.1
, pp. 41-85
-
-
Dechter, R.1
-
21
-
-
78650818467
-
Feature selection for Bayesian network classifiers using the MDL-FS score
-
M.M. Drugan, and M.A. Wiering Feature selection for Bayesian network classifiers using the MDL-FS score International Journal of Approximate Reasoning 51 6 2010 695 717
-
(2010)
International Journal of Approximate Reasoning
, vol.51
, Issue.6
, pp. 695-717
-
-
Drugan, M.M.1
Wiering, M.A.2
-
25
-
-
58149287952
-
An extension on "statistical comparisons of classifiers over multiple data sets" for all pairwise comparisons
-
S. García, and F. Herrera An extension on "Statistical comparisons of classifiers over multiple data sets" for all pairwise comparisons Journal of Machine Learning Research 9 2008 2677 2694
-
(2008)
Journal of Machine Learning Research
, vol.9
, pp. 2677-2694
-
-
García, S.1
Herrera, F.2
-
26
-
-
0001698338
-
Abductive reasoning in Bayesian belief networks using a genetic algorithm
-
E.S. Gelsema Abductive reasoning in Bayesian belief networks using a genetic algorithm Pattern Recognition Letters 16 8 1995 865 871
-
(1995)
Pattern Recognition Letters
, vol.16
, Issue.8
, pp. 865-871
-
-
Gelsema, E.S.1
-
27
-
-
7444230008
-
Discriminative Methods for Multi-labeled Classification
-
Advances in Knowledge Discovery and Data Mining
-
S. Godbole, S. Sarawagi, Discriminative methods for multi-labeled classification, in: Proceedings of the 8th Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2004, pp. 22-30. (Pubitemid 38824880)
-
(2004)
Lecture Notes in Computer Science
, Issue.3056
, pp. 22-30
-
-
Godbole, S.1
Sarawagi, S.2
-
30
-
-
52949143827
-
Label ranking by learning pairwise preferences
-
E. Hüllermeier, J. Fürnkranz, W. Cheng, and K. Brinker Label ranking by learning pairwise preferences Artificial Intelligence 172 16-17 2008 1897 1916
-
(2008)
Artificial Intelligence
, vol.172
, Issue.1617
, pp. 1897-1916
-
-
Hüllermeier, E.1
Fürnkranz, J.2
Cheng, W.3
Brinker, K.4
-
32
-
-
84897585168
-
Probabilistic model-based diagnosis
-
P. Ibargüengoytia, L.E. Sucar, E. Morales, Probabilistic model-based diagnosis, in: Proceedings of MICAI 2000, Lecture Notes in Artificial Intelligence, vol. 1793, 2000, pp. 687-698.
-
(2000)
Proceedings of MICAI 2000, Lecture Notes in Artificial Intelligence
, vol.1793
, pp. 687-698
-
-
Ibargüengoytia, P.1
-
34
-
-
0035369520
-
A general scheme for automatic generation of search heuristics from specification dependencies
-
DOI 10.1016/S0004-3702(01)00107-2, PII S0004370201001072
-
K. Kask, and R. Dechter A general scheme for automatic generation of search heuristics from specification dependencies Artificial Intelligence 129 1-2 2001 91 131 (Pubitemid 32498417)
-
(2001)
Artificial Intelligence
, vol.129
, Issue.1-2
, pp. 91-131
-
-
Kask, K.1
Dechter, R.2
-
35
-
-
0031381525
-
Wrappers for feature subset selection
-
PII S000437029700043X
-
R. Kohavi, and G. John Wrappers for feature subset selection Artificial Intelligence 97 1-2 1997 273 324 (Pubitemid 127401107)
-
(1997)
Artificial Intelligence
, vol.97
, Issue.1-2
, pp. 273-324
-
-
Kohavi, R.1
John, G.H.2
-
39
-
-
69249213986
-
AND/OR branch-and-bound search for combinatorial optimization in graphical models
-
R. Marinescu, and R. Dechter AND/OR branch-and-bound search for combinatorial optimization in graphical models Artificial Intelligence 173 16-17 2009 1457 1491
-
(2009)
Artificial Intelligence
, vol.173
, Issue.1617
, pp. 1457-1491
-
-
Marinescu, R.1
Dechter, R.2
-
41
-
-
73149118243
-
Guest editorial: Special issue on structured prediction
-
C. Parker, Y. Altun, and P. Tadepalli Guest editorial: special issue on structured prediction Machine Learning 77 2009 161 164
-
(2009)
Machine Learning
, vol.77
, pp. 161-164
-
-
Parker, C.1
Altun, Y.2
Tadepalli, P.3
-
43
-
-
84939750950
-
A probabilistic causal model for diagnostic problem solving - Part I: Integrating symbolic causal inference with numeric probabilistic inference
-
Y. Peng, and J.A. Reggia A probabilistic causal model for diagnostic problem solving - Part I: Integrating symbolic causal inference with numeric probabilistic inference IEEE Transactions on Systems, Man, and Cybernetics 17 2 1987 146 162
-
(1987)
IEEE Transactions on Systems, Man, and Cybernetics
, vol.17
, Issue.2
, pp. 146-162
-
-
Peng, Y.1
Reggia, J.A.2
-
44
-
-
0023347137
-
A probabilistic causal model for diagnostic problem solving. Part II: Diagnostic strategy
-
Y. Peng, and J.A. Reggia A probabilistic causal model for diagnostic problem solving. Part II: Diagnostic strategy IEEE Transactions on Systems, Man, and Cybernetics 17 3 1987 395 406 (Pubitemid 17632136)
-
(1987)
IEEE Transactions on Systems, Man and Cybernetics
, vol.SMC-17
, Issue.3
, pp. 395-406
-
-
Peng Yun1
Reggia James, A.2
-
46
-
-
58849103803
-
Automated heart wall motion abnormality detection from ultrasound images using Bayesian networks
-
M. Qazi,G. Fung, S. Krishnan, R. Rosales, H. Steck, R. Rao, D. Poldermans, D. Chandrasekaran, Automated heart wall motion abnormality detection from ultrasound images using Bayesian networks, in: International Joint Conference on Artificial Intelligence, 2007, pp. 519-525.
-
(2007)
International Joint Conference on Artificial Intelligence
, pp. 519-525
-
-
Qazi, M.1
Fung, G.2
Krishnan, S.3
Rosales, R.4
Steck, H.5
Rao, R.6
Poldermans, D.7
Chandrasekaran, D.8
-
50
-
-
0001457227
-
Counting labeled acyclic digraphs
-
Academic Press New York
-
R.W. Robinson Counting labeled acyclic digraphs New Directions in Graph Theory 1973 Academic Press New York
-
(1973)
New Directions in Graph Theory
-
-
Robinson, R.W.1
-
52
-
-
0006214312
-
GALGO: A genetic algorithm decision support tool for complex uncertain systems modeled with Bayesian belief networks
-
C. Rojas-Guzmán, M.A. Kramer, GALGO: a genetic algorithm decision support tool for complex uncertain systems modeled with Bayesian belief networks, in: Proceedings of the Ninth Annual Conference on Uncertainty in Artificial Intelligence, 1993, pp. 368-375.
-
(1993)
Proceedings of the Ninth Annual Conference on Uncertainty in Artificial Intelligence
, pp. 368-375
-
-
Rojas-Guzmán, C.1
-
55
-
-
0033905095
-
BoosTexter: A boosting-based system for text categorization
-
R.E. Schapire, and Y. Singer Boostexter: a boosting-based system for text categorization Machine Learning 39 2-3 2000 135 168 (Pubitemid 30594821)
-
(2000)
Machine Learning
, vol.39
, Issue.2
, pp. 135-168
-
-
Schapire, R.E.1
Singer, Y.2
-
56
-
-
0028483915
-
Finding MAPs for belief networks is NP-hard
-
S.E. Shimony Finding MAPs for belief networks is NP-hard Artificial Intelligence 68 2 1994 399 410
-
(1994)
Artificial Intelligence
, vol.68
, Issue.2
, pp. 399-410
-
-
Shimony, S.E.1
-
58
-
-
0000629975
-
Cross-validatory choice and assessment of statistical predictions (with discussion)
-
M. Stone Cross-validatory choice and assessment of statistical predictions (with discussion) Journal of the Royal Statistical Society B 36 1974 111 147
-
(1974)
Journal of the Royal Statistical Society B
, vol.36
, pp. 111-147
-
-
Stone, M.1
-
59
-
-
33947615175
-
Dynamic conditional random fields: Factorized probabilistic models for labeling and segmenting sequence data
-
C. Sutton, A. McCallum, and K. Rohanimanesh Dynamic conditional random fields: Factorized probabilistic models for labelling and segmenting sequence data Journal of Machine Learning Research 8 2007 693 723 (Pubitemid 46491655)
-
(2007)
Journal of Machine Learning Research
, vol.8
, pp. 693-723
-
-
Sutton, C.1
McCallum, A.2
Rohanimanesh, K.3
-
60
-
-
84898948585
-
Max-margin Markov networks
-
MIT Press
-
B. Taskar, C. Guestrin, D. Koller, Max-margin Markov networks, in: Advances in Neural Information and Processing Systems, vol. 16, MIT Press, 2004.
-
(2004)
Advances in Neural Information and Processing Systems
, vol.16
-
-
Taskar, B.1
Guestrin, C.2
Koller, D.3
-
61
-
-
79955562745
-
Identification of label dependencies for multi-label classification
-
L. Tenenboim, L. Rokach, B. Shapira, Identification of label dependencies for multi-label classification, in: Proceedings of the 2nd International Workshop on Learning from Multi-Label Data (MLD'10), 2010, pp. 53-60.
-
(2010)
Proceedings of the 2nd International Workshop on Learning from Multi-Label Data (MLD'10)
, pp. 53-60
-
-
Tenenboim, L.1
Rokach, L.2
Shapira, B.3
-
62
-
-
84873447495
-
Multi-label classification of music into emotions
-
K. Trohidis, G. Tsoumakas, G. Kalliris, I. Vlahavas, Multi-label classification of music into emotions, in: International Society for Music Information Retrieval Conference, 2008, pp. 325-330.
-
(2008)
International Society for Music Information Retrieval Conference
, pp. 325-330
-
-
Trohidis, K.1
Tsoumakas, G.2
Kalliris, G.3
Vlahavas, I.4
-
64
-
-
77955908068
-
Correlation-based pruning of stacked binary relevance models for multi-label learning
-
G. Tsoumakas, A. Dimou, E. Spyromitros, V. Mezaris, I., Kompatsiaris, I. Vlahavas, Correlation-based pruning of stacked binary relevance models for multi-label learning, in: Proceedings of the Workshop on Learning from Multi-Label Data (MLD'09), 2009, pp. 101-116.
-
(2009)
Proceedings of the Workshop on Learning from Multi-Label Data (MLD'09)
, pp. 101-116
-
-
Tsoumakas, G.1
Dimou, A.2
Spyromitros, E.3
Mezaris, V.4
Kompatsiaris, I.5
Vlahavas, I.6
-
66
-
-
74849083829
-
Effective and efficient multilabel classification in domains with large number of labels
-
G. Tsoumakas, I. Katakis, I. Vlahavas, Effective and efficient multilabel classification in domains with large number of labels, in: Proceedings of ECML/PKDD 2008 Workshop on Mining Multidimensional Data (MMD'08), 2008, pp. 30-44.
-
(2008)
Proceedings of ECML/PKDD 2008 Workshop on Mining Multidimensional Data (MMD'08)
, pp. 30-44
-
-
Tsoumakas, G.1
Katakis, I.2
Vlahavas, I.3
-
69
-
-
84958141402
-
Parametric mixture models for multi-labeled text
-
N. Ueda, K. Saito, Parametric mixture models for multi-labeled text, in: Advances in Neural Information Processing Systems, vol. 15, 2002, pp. 721-728.
-
(2002)
Advances in Neural Information Processing Systems
, vol.15
, pp. 721-728
-
-
Ueda, N.1
Saito, K.2
-
71
-
-
52949141834
-
Decision trees for hierarchical multi-label classification
-
C. Vens, J. Struyf, L. Schietgat, S. Džeroski, and H. Blockeel Decision trees for hierarchical multi-label classification Machine Learning 73 2 2008 185 214
-
(2008)
Machine Learning
, vol.73
, Issue.2
, pp. 185-214
-
-
Vens, C.1
Struyf, J.2
Schietgat, L.3
Džeroski, S.4
Blockeel, H.5
-
72
-
-
33947681316
-
ML-KNN: A lazy learning approach to multi-label learning
-
DOI 10.1016/j.patcog.2006.12.019, PII S0031320307000027
-
M. Zhang, and Z. Zhou ML-KNN: a lazy learning approach to multi-label learning Pattern Recognition 40 7 2007 2038 2048 (Pubitemid 46497248)
-
(2007)
Pattern Recognition
, vol.40
, Issue.7
, pp. 2038-2048
-
-
Zhang, M.-L.1
Zhou, Z.-H.2
-
73
-
-
33748366796
-
Multi-label neural networks with applications to functional genomics and text categorization
-
M.L. Zhang, and Z.H. Zhou Multi-label neural networks with applications to functional genomics and text categorization IEEE Transactions on Knowledge and Data Engineering 18 10 2006 1338 1351
-
(2006)
IEEE Transactions on Knowledge and Data Engineering
, vol.18
, Issue.10
, pp. 1338-1351
-
-
Zhang, M.L.1
Zhou, Z.H.2
|