-
1
-
-
84898958346
-
Semi-supervised support vector machines
-
Bennett, K. and Demiriz, A. Semi-supervised support vector machines. In NIPS 11, pp. 368-374. 1999.
-
(1999)
NIPS 11
, pp. 368-374
-
-
Bennett, K.1
Demiriz, A.2
-
2
-
-
0021819411
-
Thermodynamical approach to the traveling salesman problem: An efficient simulation algorithm
-
Černỳ, V. Thermodynamical approach to the traveling salesman problem: An efficient simulation algorithm. J. Opt. Theory and App., 45(1):41-51, 1985.
-
(1985)
J. Opt. Theory and App.
, vol.45
, Issue.1
, pp. 41-51
-
-
Černỳ, V.1
-
3
-
-
51949086172
-
Semi-supervised learning by low density separation
-
Chapelle, O. and Zien, A. Semi-supervised learning by low density separation. In AISTATS, pp. 57-64, 2005.
-
(2005)
AISTATS
, pp. 57-64
-
-
Chapelle, O.1
Zien, A.2
-
4
-
-
33749257143
-
A continuation method for semi-supervised SVMs
-
Chapelle, O., Chi, M., and Zien, A. A continuation method for semi-supervised SVMs. In ICML, pp. 185-192, 2006a.
-
(2006)
ICML
, pp. 185-192
-
-
Chapelle, O.1
Chi, M.2
Zien, A.3
-
5
-
-
33749252873
-
-
MIT Press, Cambridge, MA
-
Chapelle, O., Schölkopf, B., and Zien, A. (eds.). Semi-Supervised Learning. MIT Press, Cambridge, MA, 2006b.
-
(2006)
Semi-Supervised Learning
-
-
Chapelle, O.1
Schölkopf, B.2
Zien, A.3
-
6
-
-
84864069202
-
Branch and bound for semi-supervised support vector machines
-
Chapelle, O., Tubingen, G., Sindhwani, V., and Keerthi, S. S. Branch and bound for semi-supervised support vector machines. In NIPS 20, pp. 217-224. 2007.
-
(2007)
NIPS 20
, pp. 217-224
-
-
Chapelle, O.1
Tubingen, G.2
Sindhwani, V.3
Keerthi, S.S.4
-
7
-
-
41549144249
-
Optimization techniques for semi-supervised support vector machines
-
Chapelle, O., Sindhwani, V., and Keerthi, S. S. Optimization techniques for semi-supervised support vector machines. J. Mach. Learn. Res., 9:203-233, 2008. (Pubitemid 351469022)
-
(2008)
Journal of Machine Learning Research
, vol.9
, pp. 203-233
-
-
Chapelle, O.1
Sindhwani, V.2
Keerthi, S.S.3
-
8
-
-
1942452771
-
Semi-supervised learning of mixture models
-
Cozman, F., Cohen, I., and Cirelo, M. Semi-supervised learning of mixture models. In ICML, pp. 99-106, 2003.
-
(2003)
ICML
, pp. 99-106
-
-
Cozman, F.1
Cohen, I.2
Cirelo, M.3
-
9
-
-
84898975526
-
Convex methods for transduction
-
De Bie, T. and Cristianini, N. Convex methods for transduction. In NIPS 16, pp. 73-80. 2004.
-
(2004)
NIPS 16
, pp. 73-80
-
-
De Bie, T.1
Cristianini, N.2
-
10
-
-
78049531090
-
Combining labelled and unlabelled data: A case study on fisher kernels and transductive inference for biological entity recognition
-
Goutte, C., Déjean, H., Gaussier, E., Cancedda, N., and Renders, J.M. Combining labelled and unlabelled data: A case study on fisher kernels and transductive inference for biological entity recognition. In CoNLL, pp. 1-7, 2002.
-
(2002)
CoNLL
, pp. 1-7
-
-
Goutte, C.1
Déjean, H.2
Gaussier, E.3
Cancedda, N.4
Renders, J.M.5
-
11
-
-
84898928156
-
Semi-supervised learning by entropy minimization
-
Grandvalet, Y. and Bengio, Y. Semi-supervised learning by entropy minimization. In NIPS 17, pp. 529-536. 2005.
-
(2005)
NIPS 17
, pp. 529-536
-
-
Grandvalet, Y.1
Bengio, Y.2
-
12
-
-
1942483137
-
Transductive inference for text classification using support vector machines
-
Joachims, T. Transductive inference for text classification using support vector machines. In ICML, pp. 200-209, 1999.
-
(1999)
ICML
, pp. 200-209
-
-
Joachims, T.1
-
13
-
-
8844252509
-
Transductive support vector machines and applications in bioinformatics for promoter recognition
-
Kasabov, N. and Pang, S. Transductive support vector machines and applications in bioinformatics for promoter recognition. In ICNNSP, pp. 1-6, 2004.
-
(2004)
ICNNSP
, pp. 1-6
-
-
Kasabov, N.1
Pang, S.2
-
14
-
-
0343136966
-
Optimization by simulated annealing: Quantitative studies
-
Kirkpatrick, S. Optimization by simulated annealing: Quantitative studies. J. Stat. Phys., 34(5):975-986, 1984.
-
(1984)
J. Stat. Phys.
, vol.34
, Issue.5
, pp. 975-986
-
-
Kirkpatrick, S.1
-
16
-
-
71149093081
-
Semi-supervised learning using label mean
-
Li, Y.-F., Kwok, J. T., and Zhou, Z.-H. Semi-supervised learning using label mean. In ICML, pp. 633-640, 2009a.
-
(2009)
ICML
, pp. 633-640
-
-
Li, Y.-F.1
Kwok, J.T.2
Zhou, Z.-H.3
-
17
-
-
84862291617
-
Tighter and convex maximum margin clustering
-
Li, Y.-F., Tsang, I. W., Kwok, J. T., and Zhou, Z.-H. Tighter and convex maximum margin clustering. In AISTATS, pp. 344-351, 2009b.
-
(2009)
AISTATS
, pp. 344-351
-
-
Li, Y.-F.1
Tsang, I.W.2
Kwok, J.T.3
Zhou, Z.-H.4
-
18
-
-
0033886806
-
Text classification from labeled and unlabeled documents using EM
-
Nigam, K., McCallum, A. K., Thrun, S., and Mitchell, T. Text classification from labeled and unlabeled documents using EM. Mach. Learn., 39(2-3):103-134, 2000. (Pubitemid 30594822)
-
(2000)
Machine Learning
, vol.39
, Issue.2
, pp. 103-134
-
-
Nigam, K.1
Mccallum, A.K.2
Thrun, S.3
Mitchell, T.4
-
19
-
-
33749242620
-
Deterministic annealing for semi-supervised kernel machines
-
Sindhwani, V., Keerthi, S.S., and Chapelle, O. Deterministic annealing for semi-supervised kernel machines. In ICML, pp. 841-848, 2006.
-
(2006)
ICML
, pp. 841-848
-
-
Sindhwani, V.1
Keerthi, S.S.2
Chapelle, O.3
-
21
-
-
17744409615
-
Bootstrapping SVM active learning by incorporating unlabelled images for image retrieval
-
Wang, L., Chan, K., and Zhang, Z. Bootstrapping SVM active learning by incorporating unlabelled images for image retrieval. In CVPR, pp. 629-634, 2003.
-
(2003)
CVPR
, pp. 629-634
-
-
Wang, L.1
Chan, K.2
Zhang, Z.3
-
22
-
-
29344456217
-
Unsupervised and semi-supervised multi-class support vector machines
-
Xu, L. and Schuurmans, D. Unsupervised and semi-supervised multi-class support vector machines. In AAAI, pp. 904-910, 2005.
-
(2005)
AAAI
, pp. 904-910
-
-
Xu, L.1
Schuurmans, D.2
-
23
-
-
34547987546
-
Maximum margin clustering made practical
-
Zhang, K., Tsang, I.W., and Kwok, J.T. Maximum margin clustering made practical. In ICML, pp. 1119-1126, 2007.
-
(2007)
ICML
, pp. 1119-1126
-
-
Zhang, K.1
Tsang, I.W.2
Kwok, J.T.3
-
24
-
-
78149321430
-
The value of unlabeled data for classification problems
-
Zhang, T. and Oles, E The value of unlabeled data for classification problems. In ICML, pp. 1191-1198, 2000.
-
(2000)
ICML
, pp. 1191-1198
-
-
Zhang, T.1
Oles, E.2
-
25
-
-
70350346030
-
Ensemble learning
-
Li, S. Z. (ed.), Springer
-
Zhou, Z.-H. Ensemble learning. In Li, S. Z. (ed.), Encyclopedia of Biometrics, pp. 270-273. Springer, 2009.
-
(2009)
Encyclopedia of Biometrics
, pp. 270-273
-
-
Zhou, Z.-H.1
-
26
-
-
77956708689
-
Semi-supervised learning by disagreement
-
Zhou, Z.-H. and Li, M. Semi-supervised learning by disagreement. Knowl. Infor. Syst., 24(3):415-439, 2010.
-
(2010)
Knowl. Infor. Syst.
, vol.24
, Issue.3
, pp. 415-439
-
-
Zhou, Z.-H.1
Li, M.2
-
27
-
-
33745456231
-
-
Technical Report 1530, Dept. Comp. Sci., Univ. Wisconsin-Madison
-
Zhu, X. Semi-supervised learning literature survey. Technical Report 1530, Dept. Comp. Sci., Univ. Wisconsin-Madison, 2006.
-
(2006)
Semi-supervised Learning Literature Survey
-
-
Zhu, X.1
|