-
1
-
-
27744593981
-
The ising model is NP-complete
-
B. A. Cipra, "The Ising model is NP-complete," SIAM News, vol. 33, no. 6, 2000.
-
(2000)
SIAM News
, vol.33
, Issue.6
-
-
Cipra, B.A.1
-
2
-
-
34548386861
-
Gene prediction with conditional random fields
-
University of Massachusetts, Amherst
-
A. Culotta, D. Kulp, and A. McCallum, "Gene prediction with conditional random fields," University of Massachusetts, Amherst, Tech. Rep. UM-CS-2005-028, 2005.
-
(2005)
Tech. Rep. UM-cs-2005-028
-
-
Culotta, A.1
Kulp, D.2
McCallum, A.3
-
4
-
-
0032119668
-
The hierarchical hidden Markov model: Analysis and applications
-
S. Fine, Y. Singer, and N. Tishby, "The hierarchical hidden markov model: Analysis and applications," Machine Learning, vol. 32, no. 1, pp. 41-62, 1998.
-
(1998)
Machine Learning
, vol.32
, Issue.1
, pp. 41-62
-
-
Fine, S.1
Singer, Y.2
Tishby, N.3
-
5
-
-
30244555119
-
Inference in belief networks: A procedural guide
-
C. Huang and A. Darwiche, "Inference in belief networks: A procedural guide," International Journal of Approximate Reasoning, vol. 15, no. 3, pp. 225-263, 1996.
-
(1996)
International Journal of Approximate Reasoning
, vol.15
, Issue.3
, pp. 225-263
-
-
Huang, C.1
Darwiche, A.2
-
6
-
-
0042357355
-
Basic methods of probabilistic context free grammars
-
Springer Verlag
-
F. Jelinek, J. D. Lafferty, and R. L. Mercer, "Basic methods of probabilistic context free grammars," in Speech Recognition and Understanding. Recent Advances, Trends, and Applications. Springer Verlag, 1992.
-
(1992)
Speech Recognition and Understanding. Recent Advances, Trends, and Applications
-
-
Jelinek, F.1
Lafferty, J.D.2
Mercer, R.L.3
-
7
-
-
0041177734
-
-
Ph.D. dissertation, Massachusetts Institute of Technology, Cambridge, MA, USA
-
R. H. Kassel, "A comparison of approaches to on-line handwritten character recognition," Ph.D. dissertation, Massachusetts Institute of Technology, Cambridge, MA, USA, 1995.
-
(1995)
A Comparison of Approaches to On-line Handwritten Character Recognition
-
-
Kassel, R.H.1
-
8
-
-
0142192295
-
Conditional random fields: Probabilistic models for segmenting and labeling sequence data
-
J. Lafferty, A. McCallum, and F. Pereira, "Conditional random fields: Probabilistic models for segmenting and labeling sequence data," in Proceedings of the Eighteenth International Conference on Machine Learning, 2001, pp. 282-289.
-
(2001)
Proceedings of the Eighteenth International Conference on Machine Learning
, pp. 282-289
-
-
Lafferty, J.1
McCallum, A.2
Pereira, F.3
-
11
-
-
71149101799
-
Sparse higher order conditional random fields for improved sequence labeling
-
X. Qian, X. Jiang, Q. Zhang, X. Huang, and L. Wu, "Sparse higher order conditional random fields for improved sequence labeling," in ICML, 2009, p. 107.
-
(2009)
ICML
, pp. 107
-
-
Qian, X.1
Jiang, X.2
Zhang, Q.3
Huang, X.4
Wu, L.5
-
13
-
-
84898962087
-
Semi-Markov conditional random fields for information extraction
-
Cambridge, MA: MIT Press
-
S. Sarawagi and W. W. Cohen, "Semi-Markov conditional random fields for information extraction," in Advances in Neural Information Processing Systems 17. Cambridge, MA: MIT Press, 2005, pp. 1185-1192.
-
(2005)
Advances in Neural Information Processing Systems
, vol.17
, pp. 1185-1192
-
-
Sarawagi, S.1
Cohen, W.W.2
-
15
-
-
84898948585
-
Max-margin Markov networks
-
Cambridge, MA: MIT Press
-
B. Taskar, C. Guestrin, and D. Koller, "Max-margin Markov networks," in Advances in Neural Information Processing Systems 16. Cambridge, MA: MIT Press, 2004.
-
(2004)
Advances in Neural Information Processing Systems
, vol.16
-
-
Taskar, B.1
Guestrin, C.2
Koller, D.3
-
17
-
-
79952553416
-
Hierarchical semi-Markov conditional random fields for recursive sequential data
-
Cambridge, MA: MIT Press
-
T. T. Tran, D. Phung, H. Bui, and S. Venkatesh, "Hierarchical semi-Markov conditional random fields for recursive sequential data," in NIPS'08: Advances in Neural Information Processing Systems 20. Cambridge, MA: MIT Press, 2008, pp. 1657-1664.
-
(2008)
NIPS'08: Advances in Neural Information Processing Systems
, vol.20
, pp. 1657-1664
-
-
Tran, T.T.1
Phung, D.2
Bui, H.3
Venkatesh, S.4
-
18
-
-
14344250451
-
Support vector machine learning for interdependent and structured output spaces
-
I. Tsochantaridis, T. Hofmann, T. Joachims, and Y. Altun, "Support vector machine learning for interdependent and structured output spaces," in Proceedings of the Twenty-First international conference on Machine learning, 2004, pp. 104-112.
-
(2004)
Proceedings of the Twenty-first International Conference on Machine Learning
, pp. 104-112
-
-
Tsochantaridis, I.1
Hofmann, T.2
Joachims, T.3
Altun, Y.4
|