Reading list
- Machine Learning: A Probabilistic Perspective. Kevin P. Murphy, 2012.
- The Expectation Maximization Algorithm: A short tutorial, Sean Borman, 2004.
- Speech and Language Processing, Chapter 8. Daniel Jurafsky and James H. Martin, 2014.
- Bayesian inference with tears, Kevin Knight, 2009.
- Gibbs sampling for the uninitiated, Resnik and Hardisty, 2010.
- Latent Dirichlet Allocation, Blei et al., 2003.
- Tutorial: Variational inference for machine learning
- High-Level Explanation of Variational Inference