Graphical Models

See my comments inline:
1. Kevin Murphy's introduction to graphical models (great for beginners) Link
2. Dietterich tutorial on sequential machine learning (not very technical) Link
3. Blei's- A Tutorial on Bayesian Nonparametric Models (great for beginner's, discusses BNP version of factor and cluster models) Link
4. Original LDA paper (think everyone should read it, very beautifully written) Link
5. Bayesian Modelling in Machine Learning: A Tutorial Review (quite good and comprehensive and I loved the short 1-2 liners about different concepts) Link
6. Tom Minka's PhD thesis (good introduction to variational methods in Ch1 and Ch2) Link
7. Kevin Murphy's book on ML (great source. I will give a +1 over Bishop in it's ease of understanding while being comprehensive) Link
8. G Henreich's: Parameter Estimation for text Analysis (best introduction to read about LDA, gibbs sampling and usual distributions) Link