1. Wei Chen
  2. data-science-seminar

Overview

data-science-seminar
====================

Literature survey of Topic Model. 

## LSA/LSI
* general
    1. Deerwester, Scott C., et al. "Indexing by latent semantic analysis." JASIS 41.6 (1990): 391-407.
    2. Landauer, Thomas K., Peter W. Foltz, and Darrell Laham. "An introduction to latent semantic analysis." Discourse processes 25.2-3 (1998): 259-284.
* SVD
    1. Intuitive geometry interpretation: http://www.ams.org/samplings/feature-column/fcarc-svd

## pLSA
1. Hofmann, Thomas. "Probabilistic latent semantic analysis." Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence. Morgan Kaufmann Publishers Inc., 1999.

## LDA
* general
    1. Blei, David M., Andrew Y. Ng, and Michael I. Jordan. "Latent dirichlet allocation." the Journal of machine Learning research 3 (2003): 993-1022.
* inference
    1. Variable elimination(paper?)
    2. Gibbs sampling(paper?)
    3. Variational Inference
        1. Jordan, Michael I., et al. An introduction to variational methods for graphical models. Springer Netherlands, 1998.
        2. Wainwright, Martin J., and Michael I. Jordan. "Graphical models, exponential families, and variational inference." Foundations and Trends® in Machine Learning 1.1-2 (2008): 1-305.
* parameter estimation
    1. Heinrich, Gregor. "Parameter estimation for text analysis." Web: http://www. arbylon. net/publications/text-est. pdf (2005).