Under review
- Semi-supervised CONTRAfold for RNA secondary structure prediction:
A maximum entropy approach
M. Tan, J. Feng, S. Wang. and M. Raymer. [pdf]
2013
- Direct 0-1 loss minimization and margin maximization with boosting
S. Zhai, T. Xia, M. Tan and S. Wang
Advances in Neural Information Processing Systems, NIPS-2013, [pdf]
- Consistency and generalization bounds for maximum entropy density estimation
S. Wang, R. Greiner and S. Wang.
Entropy: Special Issue on Maximum Entropy and Bayes Theorem, Vol. 15, No. 12, pp. 5439-5463, 2013.
[pdf]
- Improving alignment of system combination by using multi-objective optimization
T. Xia, Z. Ji, S. Zhai, Y. Chen, Q. Liu and S. Wang
Conference on Empirical Methods in Natural Language Processing, EMNLP-2013, [pdf]
- A corpus level MIRA tuning strategy for machine translation
M. Tan, T. Xia, S. Wang and B. Zhou
Conference on Empirical Methods in Natural Language Processing, EMNLP-2013, [pdf]
- A robust semi-supervised boosting method using linear programming
S. Zhai, T. Xia, M. Tan, S. Wang and P. Zhang
IEEE GlobalSIP Symposium on Optimization in Machine Learning and Signal Processing, GlobalSIP-2013.
- Direct optimization of ranking measures for learning to rank models
M. Tan, T. Xia, L. Guo and S. Wang
The 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD-2013, [pdf]
2012
- Extracting diverse sentiment expressions with target-dependent polarity from Twitter
L. Chen, W. Wang, M. Nagarajan, S. Wang and A. Sheth The Sixth International Conference on Weblogs and Social Media, ICWSM-2012, [pdf]
- A scalable distributed syntactic, semantic and lexical language model
M. Tan, W. Zhou, L. Zheng and S. Wang Computational Linguistics, Vol. 38, No. 3, pp. 631-671, 2012, [pdf]
- The latent maximum entropy principle
S. Wang,
D. Schuurmans and Y. Zhao. ACM Transactions on Knowledge Discovery from Data (TKDD), Vol. 6, No. 2, 8:1-42, 2012, [pdf]
- Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields
S. Wang, S. Wang, L. Cheng, R. Greiner and D. Schuurmans Computational Intelligence, 2012.
2011
- A large scale distributed syntactic, semantic and lexical
language model for machine translation
M. Tan, W. Zhou,
L. Zheng and S. Wang
The 49th Annual Meeting of the Association for Computational Linguistics:
Human Language Technologies, ACL-2011. [pdf]
2009
- A rate distortion approach for semi-supervised conditional random fields
Y. Wang, G. Haffari, S. Wang and G. Mori
Advances in Neural Information Processing Systems, NIPS-2009. [pdf]
- Monetizing user activity on social networks - challenges and experiences
M. Nagarajan, K. Baid, A. P. Sheth, and S. Wang The IEEE/WIC/ACM International Conference on Web Intelligence, WI-2009.
- Information theoretic regularization for semi-supervised boosting
L. Zheng, S. Wang, Y. Liu and C. Lee The 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD-2009.[pdf]
2008
- Boosting with incomplete information
G. Haffari, Y. Wang, S. Wang, G. Mori and F. Jiao The 25th International Conference on Machine Learning, ICML-2008. [pdf]
- Segmenting brain tumors using pseudo--conditional random fields
C. Lee, S. Wang, A. Murtha, M. Brown and R. Greiner The 11th International
Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI-2008. [pdf]
- Constrained classification on structured data
C. Lee, M. Brown, R. Greiner, S. Wang and A. Murtha The 23th AAAI Conference on Artificial Intelligence, AAAI-2008.
- Unsupervised discovery of compound entities for relationship extraction
C. Ramakrishnan, P. Mendes, S. Wang and A. Sheth The 16th International Conference on Knowledge Engineering and Knowledge Management Knowledge Patterns, EKAW-2008.
2007
- Learning to model spatial dependency: Semi-supervised
discriminative random fields
C. Lee, S. Wang, F. Jiao, D.
Schuurmans and R. Greiner Advances in Neural Information
Processing Systems, NIPS-2007. [pdf]
- Implicit online learning with kernels
L. Cheng,
S. Vishwanathan, D. Schuurmans, S. Wang and T. Caelli Advances in
Neural Information Processing Systems, NIPS-2007. [pdf]
2006
- Almost sure convergence of Titterington's recursive
estimator for finite mixture
S. Wang and Y.
Zhao Statistics & Probability Letters, Vol. 76, No. 18,
pp. 2001-2006, December 2006. [pdf]
- Stochastic analysis of lexical and semantic enhanced
structural language model
S. Wang, S. Wang, L. Cheng, R.
Greiner and D. Schuurmans The 8th International Colloquium on
Grammatical Inference, ICGI-2006. [pdf]
- Semi-supervised conditional random fields for improved
sequence segmentation and labeling
F. Jiao, S. Wang, C. Lee,
R. Greiner and D. Schuurmans The Joint 21st International
Conference on Computational Linguistics and 44th Annual Meeting of the
Association for Computational Linguistics, COLING/ACL-2006. [pdf]
- Using query-specific variance estimates to combine Bayesian
classifiers
C. Lee, R. Greiner and S. Wang The 23th
International Conference on Machine Learning, ICML-2006. [pdf]
- An online discriminative approach to background
subtraction
L. Cheng, S. Wang, D. Schuurmans, T. Caelli and
S. Vishwanathan IEEE International Conference on Advanced Video
and Signal Based Surveillance, AVSS-2006. [pdf]
2005
- Exploiting syntactic, semantic and lexical regularities in
language modeling via directed Markov random fields
S.
Wang, S. Wang, R. Greiner, D. Schuurmans and L. Cheng The 22th
International Conference on Machine Learning, ICML-2005. [pdf]
- Variational Bayesian image modelling
L. Cheng,
F. Jiao, D. Schuurmans and S. Wang The 22th International
Conference on Machine Learning, ICML-2005. [pdf]
- Combining statistical language models via the latent maximum
entropy principle
S. Wang, D. Schuurmans, F. Peng and Y.
Zhao Machine Learning Journal: Special Issue on Learning in
Speech and Language Technologies, Vol. 60, pp. 229-250, 2005. [pdf]
2004
- Learning mixture models with the regularized latent maximum
entropy principle
S. Wang, D. Schuurmans, F. Peng and Y.
Zhao IEEE Trans. on Neural Networks: Special Issue on Information
Theoretic Learning, Vol. 15, No. 4, pp. 903-916, 2004. [pdf]
- Augmenting naive Bayes text classifier using statistical
n-gram language modeling
F. Peng, D. Schuurmans and S.
Wang Information Retrieval, Vol. 7, No. 3-4, pp. 317-345,
2004. [pdf]
2003
- Learning continuous latent variable models with Bregman
divergence
S. Wang and D. Schuurmans The 14th
International Conference on Algorithmic Learning Theory, ALT-2003.
[pdf]
- Boltzmann machine learning with the latent maximum entropy
principle
S. Wang, D. Schuurmans, F. Peng and Y.
Zhao The Nineteenth Conference on Uncertainty in Artificial
Intelligence, UAI-2003. [ps]
- Learning mixture models with the latent maximum entropy
principle
S. Wang, D. Schuurmans, F. Peng and Y.
Zhao The 20th International Conference on Machine Learning,
ICML-2003. [ps]
- Semantic n-gram language modeling with the latent maximum
entropy principle
S. Wang, D. Schuurmans, F. Peng and Y.
Zhao International Conference on Acoustics, Speech, ans Signal
Processing, ICASSP-2003. [ps]
- Language and task independent text categorization with
simple language models
F. Peng, D. Schuurmans, S.
Wang North American Chapter of the Association for Computational
Linguistics, NAACL-2003.
- Language independent authorship attribution with character
level n-Gram language modeling
F. Peng, D. Schuurmans, S.
Wang The 10th Conference of the European Chapter of the
Association for Computational Linguistics, EACL-2003.
2002
- The latent maximum entropy principle
S. Wang,
R. Rosenfeld, Y. Zhao and D. Schuurmans IEEE International
Symposium on Information Theory, ISIT-2002. Abstract[ps], [ps]
- Almost sure convergence of Titterington's recursive
estimator for finite mixture models
S. Wang and Y.
Zhao IEEE International Symposium on Information Theory,
ISIT-2002.
- Predicting oral reading miscues
J. Mostow, J.
Beck, V. Winter, S. Wang and B. Tobin International Conference on
Spoken Language Processing, ICSLP-2002.
2001
- On-line Bayesian tree-structured transformation of HMMs with
optimal model selection for speaker adaptation
S. Wang and
Y. Zhao IEEE Trans. on Speech and Audio Processing, Vol. 9,
No. 6, pp. 663-677, September 2001. [pdf]
- Latent maximum entropy principle for statistical language
modeling
S. Wang, R. Rosenfeld and Y. Zhao IEEE
Workshop on Automatic Speech Recognition and Understanding,
ASRU-2001.
- Recursive estimation of time-varying environments for robust
speech recognition
Y. Zhao, S. Wang and K. Yen IEEE
International Conference on Acoustics, Speech, and Signal Processing,
ICASSP-2001.
2000
- Optimal on-line Bayesian model selection for speaker
adaptation
S. Wang and Y. Zhao International
Conference on Spoken Language Processing, ICSLP-2000.
- On-line Bayesian speaker adaptation by using tree-structured
transformation and robust priors
S. Wang and Y.
Zhao IEEE International Conference on Acoustics, Speech, and
Signal Processing, ICASSP-2000.
1999
- On-line Bayesian tree-structured transformation of hidden
Markov models for speaker adaptation
S. Wang and Y.
Zhao IEEE Workshop on Automatic Speech Recognition and
Understanding, ASRU-1999.
- A unified framework for recursive maximum likelihood
estimation of hidden Markov models
S. Wang and Y.
Zhao The 33rd Annual Conference on Information Sciences and
Systems, CISS-1999.
1998
- On convergence of maximum likelihood estimation of binary
HMMs by EM algorithm
M. Li, S. Wang and Y. Zhao The
32rd Annual Conference on Information Sciences and Systems,
CISS-1998, pp. 1018-1024.
1995
- Short-term generation scheduling with transmission and
environmental constraints using an augmented Lagrangian
relaxation
S. Wang, S. Shahidehpour, D. Kirschen, S.
Mokhtari and G. Irisarri IEEE Trans. on Power Systems, Vol.
10, No. 3, pp. 1294-1301, August 1995. [pdf]
- Probabilistic marginal cost curve and its
applications
S. Wang, S. Shahidehpour and N.
Xiang IEEE Trans. on Power Systems, Vol. 10, No. 3, pp
1321-1328, August 1995. [pdf]
Manuscript
- On determination of domains of convergence for the EM
algorithm
S. Wang and Y. Zhao [ps]
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