On nonparametric Bayesian modeling and inference, including various versions of "Chinese restaurant process priors" that allow flexible structures to be learned and that allow sharing of statistical strength among sets of related structures.

Python module for Markov chain Monte Carlo sampling (Metropolis-Hastings).

Suggests that simplicity may not be as good a bias for our world as commonly believed.

Automated scientific discovery: By putting large databases of papers in machine-readable format, it is possible to do automated inferences from them.

Topics: Introduction to Statistical Machine Learning, Foundations, Kernel Methods, Inference in Graphical Models, Contrast Data Mining.

A quantitative theory that treats evolution as a form of computational learning. Doing away with the distinction between learned and inherent (evolved) knowledge, cognitive systems can be viewed as pure learning systems.

"A forum for reinforcement learning researchers to rigorously compare the performance of their methods on a suite of challenging domains."

Elefant (Efficient Learning, Large-scale Inference, and Optimization Toolkit) is an open source library for machine learning licensed under the Mozilla Public License.

From foundations of algorithmic information theory to asymptotically optimal yet infeasible methods showing the ultimate limits of machine learning, and all the way down to practically useful tricks for recurrent nets.

"We focus on learning agents interacting with an initially unknown world. Since the world is dynamic, unlike many other machine learning courses ours will put strong emphasis on learning to deal with sequential data."