Here are the slides of presentations which I've given.

A tale of two bounds

The connection between information theory and learning theory

Nonlinear Dimensionality Reduction

Correlated Equilibria and Graphical Games

A tutorial on sample complexity bounds

Tightness of machine learning bounds (lyx,tex, ps)
Compiling planners (lyx,tex, ps)
Planning (lyx,tex, ps)
Parallelization of computations on grids.
Cribbage (lyx,tex, ps)
improved margin bound
PAC stability bounds
Maximum Entropy
Tight sample complexity bounds
Decision theoretic particle filters
Spam detection
Proofs of learning
Conservative Policy Iteration (lyx)
Generative vs. Discriminative classification (lyx)
PAC-Bayes lyx, tex
Introductory PAC lyx, tex
Stochastic Neural Nets lyx, tex
Train and Test bounds lyx, tex
PAC-Bayes and margin bounds lyx, tex