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Shaojun Wang, Shaomin Wang, Russell Greiner, Dale Schuurmans, Li Cheng. Exploiting Syntactic, Semantic and Lexical Regularities in Language Modeling via Directed Markov Random Fields. In International Symposium on Chinese Spoken Language Processing (ISCSLP). Singapore, Singapore; 2004.
L. Cheng, D. Schuurmans, R. Greiner, Shaojun Wang, Shaojun Wang. Exploiting Syntactic, Semantic and Lexical Regularities in Language Modeling via Directed Markov Random Fields. In Exploiting Syntactic, Semantic and Lexical Regularities in Language Modeling via Directed Markov Random Fields. 2005.
L. Cheng, D. Schuurmans, R. Greiner, Shaojun Wang, Shaojun Wang. Exploiting Syntactic, Semantic and Lexical Regularities in Language Modeling via Directed Markov Random Fields. In Exploiting Syntactic, Semantic and Lexical Regularities in Language Modeling via Directed Markov Random Fields. 2005.
Lu Chen, Wenbo Wang, Meenakshi Nagarajan, Shaojun Wang, Amit Sheth. Extracting Diverse Sentiment Expressions with Target-dependent Polarity from Twitter. In International AAAI Conference on Weblogs and Social Media (ICWSM). Dublin, Ireland: In Proceedings of the 6th International AAAI Conference on Weblogs and Social Media (ICWSM); 2012.  (220.53 KB)
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Shaojun Wang, F. Peng, D. Schuurmans. Language and Task Independent Text Categorization Using Character Level N-Gram Language Models. 2003 ;.
F. Peng, Shaojun Wang, D. Schuurmans. Language Independent Automated Authorship Attribution with Character Level N-Gram Language Modeling. In Language Independent Automated Authorship Attribution with Character Level N-Gram Language Modeling. 2003.
F. Peng, D. Schuurmans, Shaojun Wang. Latent Maximum Entropy Approach for Semantic N-gram Language Modeling. In 2003.
Shaojun Wang, Y. Zhao, D. Schuurmans, R. Rosenfeld. The Latent Maximum Entropy Principle. In The Latent Maximum Entropy Principle. 2002.
Shaojun Wang, Y. Zhao, R. Rosenfeld. Latent Maximum Entropy Principle for Statistical Language Modeling. In 2001.
Shaojun Wang, D. Schuurmans. Learning Continuous Latent Variable Models with Bregman Divergences. In Learning Continuous Latent Variable Models with Bregman Divergences. 2003.
Shaojun Wang, D. Schuurmans. Learning Latent Variable Models with Bregman Divergences. In Learning Latent Variable Models with Bregman Divergences. 2003.
Y. Zhao, Shaojun Wang, F. Peng, D. Schuurmans. Learning Mixture Models with the Latent Maximum Entropy Principle. In Learning Mixture Models with the Latent Maximum Entropy Principle. 2003.
D. Schuurmans, F. Peng, Y. Zhao, Shaojun Wang. Learning Mixture Models with the Regularized Latent Maximum Entropy Principle. 2004 ;.  (0 bytes)
F. Jiao, D. Schuurmans, R. Greiner, C. Lee, Shaojun Wang. Learning to Model Spatial Dependency: Semi-Supervised Discriminative Random Fields. 2007 ;.
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Shaojun Wang, Y. Zhao. A Unifed Framework for Recursive Maximum Likelihood Estimation of Hidden Markov Models. In A Unifed Framework for Recursive Maximum Likelihood Estimation of Hidden Markov Models. 1999.

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