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Topic Models

Last week I met with a long-lost friend in ICASSP 2010 held in Dallas, TX. More precisely, the very nice friend of mine, Duangmanee (Pew), was my senior student when we were in the same high-school. In the conference, we had a good time (almost an hour) discussing about our lives, updates on our others friends (heeheehee…a nice way to say “gossips”) and our research, and I’m very lucky that Pew is an expert on Topic Models that I’m interested in. Since I’m a beginner on this topic, so I think I will have to learn some more fundamental works on this topic first prior to understanding Pew’s paper.

This post is my effort to list all good papers, notes and tutorials on topic models in the hope that it might be useful for other beginners like me. Please feel free to suggest in order to make this post of the most useful to learners.

Video lecture

Topic Models

David Blei
2 videos

Independent Factor Topic Models

Duangmanee (Pew) Putthividhya

Useful links (I’m working on the list)

LDA on Wiki

Blei, David M.; Ng, Andrew Y.; Jordan, Michael I; Lafferty, John (January 2003). “Latent Dirichlet allocation”. Journal of Machine Learning Research 3: pp. 993–1022. doi:10.1162/jmlr.2003.3.4-5.993

Blei, David M.; Lafferty, John D. (2006). “Correlated topic models”. Advances in Neural Information Processing Systems

D. Blei and M. Jordan. Modeling annotated data. In Proceedings of the 26th annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 127–134. ACM Press, 2003. [PDF]

K. Barnard, P. Duygulu, N. de Freitas, D. Forsyth, D. Blei, and M. Jordan. Matching words and pictures. Journal of Machine Learning Research, 3:1107–1135, 2003. [PDF]

Blei, David M.; Jordan, Michael I.; Griffiths, Thomas L.; Tenenbaum; Joshua B (2004). “Hierarchical Topic Models and the Nested Chinese Restaurant Process”. Advances in Neural Information Processing Systems 16: [pdf]

Hanna M. Wallach (2008), “Structured Topic Model for Language” [PhD thesis]

Tomoharu Iwata, Takeshi Yamada, Naonori Ueda, “Modeling Social Annotation Data with Content Relevance using a Topic Model,” Advances in Neural Information Processing Systems (NIPS2009), 835-843, 2009 [pdf]

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