-
1
-
-
68949104188
-
Discriminative learning for label sequences via boosting
-
MIT Press
-
Altun, Y., Hofmann, T., & Johnson, M. Discriminative learning for label sequences via boosting. In NIPS 15. MIT Press, 2002.
-
(2002)
NIPS
, vol.15
-
-
Altun, Y.1
Hofmann, T.2
Johnson, M.3
-
2
-
-
85113387701
-
Investigating loss functions and optimization methods for discriminative learning of label sequences
-
Altun, Y., Johnson, M., & Hofmann, T. Investigating loss functions and optimization methods for discriminative learning of label sequences. In Proc. EMNLP. ACL, 2003.
-
(2003)
Proc. EMNLP. ACL
-
-
Altun, Y.1
Johnson, M.2
Hofmann, T.3
-
3
-
-
27844439373
-
A framework for learning predictive structures from multiple tasks and unlabeled data
-
Ando, R. K. & Zhang, T. A framework for learning predictive structures from multiple tasks and unlabeled data. Journal of Machine Learning Research, 6:pp. 1817-1853, 2005.
-
(2005)
Journal of Machine Learning Research
, vol.6
, pp. 1817-1853
-
-
Ando, R.K.1
Zhang, T.2
-
4
-
-
33745832304
-
A PAC-style model for learning from labeled and unlabeled data
-
Balcan, M. & Blum, A. A PAC-style model for learning from labeled and unlabeled data. In Proc. COLT. 2005.
-
(2005)
Proc. COLT
-
-
Balcan, M.1
Blum, A.2
-
5
-
-
84860524227
-
Bollywood, boom-boxes and blenders: Domain adaptation for sentiment classification
-
Blitzer, J., Dredze, M., & Pereira, F. Biographies, bollywood, boom-boxes and blenders: Domain adaptation for sentiment classification. In Proc. ACL. ACL, 2007.
-
(2007)
Proc. ACL. ACL
-
-
Blitzer, J.1
Dredze, M.2
Biographies, P.F.3
-
6
-
-
80053342456
-
Domain adaptation with structural correspondence learning
-
Blitzer, J., McDonald, R., & Pereira, F. Domain adaptation with structural correspondence learning. In Proc. EMNLP. 2006.
-
(2006)
Proc. EMNLP
-
-
Blitzer, J.1
McDonald, R.2
Pereira, F.3
-
7
-
-
0031620208
-
Combining labeled and unlabeled data with co-training
-
Blum, A. & Mitchell, T. Combining labeled and unlabeled data with co-training. In COLT. 1998.
-
(1998)
COLT
-
-
Blum, A.1
Mitchell, T.2
-
8
-
-
0020192214
-
A multiplicative formula for aggregating probability assessments
-
Bordley, R. F. A multiplicative formula for aggregating probability assessments. Management Science, 28(10):pp. 1137-1148, 1982.
-
(1982)
Management Science
, vol.28
, Issue.10
, pp. 1137-1148
-
-
Bordley, R.F.1
-
10
-
-
33749252873
-
-
The MIT Press
-
Chapelle, O., Schölkopf, B., & Zien, A., eds. Semi-Supervised Learning (Adaptive Computation and Machine Learning). The MIT Press, 2006.
-
(2006)
Semi-Supervised Learning (Adaptive Computation and Machine Learning)
-
-
Chapelle, O.1
Schölkopf, B.2
Zien, A.3
-
11
-
-
85119383022
-
Unsupervised models for named entity classification
-
Collins, M. & Singer, Y. Unsupervised models for named entity classification. In Proc. SIGDATEMNLP. ACL, 1999.
-
(1999)
Proc. SIGDATEMNLP. ACL
-
-
Collins, M.1
Singer, Y.2
-
12
-
-
85162012703
-
Expectation maximization and posterior constraints
-
MIT Press
-
Graca, J., Ganchev, K., & Taskar, B. Expectation maximization and posterior constraints. In NIPS 20. MIT Press, 2008.
-
(2008)
NIPS 20
-
-
Graca, J.1
Ganchev, K.2
Taskar, B.3
-
13
-
-
84860537772
-
Semi-supervised conditional random fields for improved sequence segmentation and labeling
-
ACL, Morristown, NJ, USA
-
Jiao, F., Wang, S., Lee, C.-H., Greiner, R., & Schuurmans, D. Semi-supervised conditional random fields for improved sequence segmentation and labeling. In Proc. ACL, pp. 209-216. ACL, Morristown, NJ, USA, 2006.
-
(2006)
Proc. ACL
, pp. 209-216
-
-
Jiao, F.1
Wang, S.2
Lee, C.-H.3
Greiner, R.4
Schuurmans, D.5
-
14
-
-
65249157560
-
The divergence and bhattacharyya distance measures in signal selection
-
Kailath, T. The divergence and bhattacharyya distance measures in signal selection. IEEE Transactions on Communications, 15(1):pp. 52-60, 1967.
-
(1967)
IEEE Transactions on Communications
, vol.15
, Issue.1
, pp. 52-60
-
-
Kailath, T.1
-
15
-
-
38049026697
-
Multi-view regression via canonical correlation analysis
-
Springer Berlin / Heidelberg
-
Kakade, S. & Foster, D. Multi-view regression via canonical correlation analysis. In Learning Theory, vol. 4539. Springer Berlin / Heidelberg, 2007.
-
(2007)
Learning Theory
, vol.4539
-
-
Kakade, S.1
Foster, D.2
-
16
-
-
85142688646
-
Newsweeder: Learning to filter netnews
-
Lang, K. Newsweeder: Learning to filter netnews. In Proc. ICML. 1995.
-
(1995)
Proc. ICML
-
-
Lang, K.1
-
17
-
-
56449123826
-
Simple robust, scalable semi-supervised learning via expectation regularization
-
Mann, G. S. & McCallum, A. Simple, robust, scalable semi-supervised learning via expectation regularization. In Proc. ICML. 2007.
-
(2007)
Proc. ICML
-
-
Mann, G.S.1
McCallum, A.2
-
19
-
-
2142727946
-
Limitations of co-training for natural language learning from large datasets
-
Pierce, D. & Cardie, C. Limitations of co-training for natural language learning from large datasets. In Proc. EMNLP. 2001.
-
(2001)
Proc. EMNLP
-
-
Pierce, D.1
Cardie, C.2
-
20
-
-
70349185610
-
The rademacher complexity of co-regularized kernel classes
-
M. Meila & X. Shen, eds.
-
Rosenberg, D. & Bartlett, P. The rademacher complexity of co-regularized kernel classes. In M. Meila & X. Shen, eds., Proc. AI Stats. 2007.
-
(2007)
Proc. AI Stats.
-
-
Rosenberg, D.1
Bartlett, P.2
-
22
-
-
85099019865
-
Introduction to the conll-2003 shared task: Language-independent named entity recognition
-
Sang, E. F. T. K. & Meulder, F. D. Introduction to the conll-2003 shared task: language-independent named entity recognition. In Proc. HLT-NAACL. ACL, 2003.
-
(2003)
Proc. HLT-NAACL. ACL
-
-
Sang, E.F.T.K.1
Meulder, F.D.2
-
23
-
-
33749243505
-
A co-regularization approach to semi-supervised learning with multiple views
-
Sindhwani, V., Niyogi, P., & Belkin, M. A Co-Regularization Approach to Semi-supervised Learning with Multiple Views. In Workshop on Learning with Multiple Views, Proceedings of ICML. 2005.
-
(2005)
Workshop on Learning with Multiple Views, Proceedings of ICML
-
-
Sindhwani, V.1
Niyogi, P.2
Belkin, M.3
-
24
-
-
33645977859
-
Logarithmic opinion pools for conditional random fields
-
Smith, A., Cohn, T., & Osborne, M. Logarithmic opinion pools for conditional random fields. In Proc. ACL. ACL, 2005.
-
(2005)
Proc. ACL. ACL
-
-
Smith, A.1
Cohn, T.2
Osborne, M.3
-
25
-
-
85071661854
-
Semi-supervised structured output learning based on a hybrid generative and discriminative approach
-
Suzuki, J., Fujino, A., & Isozaki, H. Semi-supervised structured output learning based on a hybrid generative and discriminative approach. In Proc. EMNLP-CoNLL. 2007.
-
(2007)
Proc. EMNLP-CoNLL
-
-
Suzuki, J.1
Fujino, A.2
Isozaki, H.3
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