Jbg reading

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•	Jordan, M. Introduction to Graphical Models (Chapters 1-5, 9-12)
•	Russell, S., & Norvig, P (2002). Artificial Intelligence: A Modern Approach. New York: Prentice Hall.  (Chapters 3-7, 18-21)

http://www.cs.berkeley.edu/~russell/aima/

•	Manning, C., & Schütze, H. Statistical Natural Language Processing.  Cambridge: MIT Press. (Chapter 3-8)
•	Schutze, H. Automatic word sense discrimination. Computational Linguistics, 24(1):97-124, 1998. 

http://citeseer.ist.psu.edu/schutze98automatic.html

•	Yarowsky, D. (1999). Unsupervised Word Sense Disambiguation Rivaling Supervised Methods. Meeting of the Association for Computational Linguistics.

http://acl.ldc.upenn.edu/P/P95/P95-1026.pdf

•	Schapire, R. (2001). The Boosting Approach to Machine Learning: An Overview. In MSRI Workshop on Nonlinear Estimation and Classification, Berkeley, CA, Mar. 2001. 

http://citeseer.ist.psu.edu/schapire02boosting.html

•	Peter Stone, Robert E. Schapire, Michael L. Littman, János A. Csirik and David McAllester.  Decision-theoretic bidding based on learned density models in simultaneous, interacting auctions.  Journal of Artificial Intelligence Research, 19:209-242, 2003.

http://www.cs.princeton.edu/~schapire/uncompress-papers.cgi/bidding-jair.ps

•	Miller G.  Nouns in WordNet. (1995).  Introduction to WordNet: An On-line Lexical Database.  Cambridge: MIT Press. 
•	Fellbaum, C.  Verbs in WordNet. (1995).  Introduction to WordNet: An On-line Lexical Database.  Cambridge: MIT Press.

http://www.cfilt.iitb.ac.in/archives/english_wordnet_5papers.pdf

•	Snow, R., Jurafsky, D., & Ng, A. (2005). Learning syntactic patterns for automatic hypernym discovery. In NIPS 17. 

http://ai.stanford.edu/~ang/papers/nips04-hypernym.pdf

•	Blei, D., Ng, A., Jordan, M. (2003).  Latent Dirichlet allocation. Journal of Machine Learning Research Volume 3: 993 - 1022.

http://portal.acm.org/citation.cfm?id=944937&jmp=cit&coll=portal&dl=ACM&CFID=75235706&CFTOKEN=5982316#CIT

•	Winn, J., & Bishop, C.M. (2005). Variational message passing. Journal of Machine Learning Research  6, 661–694.

http://research.microsoft.com/Bib2html/downloads/Bishop-VIBES-JMLR-04.pdf

•	Teh, Y. Jordan, M. Beal, M., & Blei, D. (2005). Hierarchical Dirichlet processes. Journal of the American Statistical Association.

http://www.cs.princeton.edu/~blei/papers/TehJordanBealBlei2004.pdf