MLSS Slides and Codes

This page provides downloadable material such as slides and codes for the MLSS program.

Videos of MLSS talks are available on YouTube at the MLSS Iceland 2014 channel


Neil Lawrence: Introduction to Machine Learning

Material: slides

Yoshua Bengio: Deep Learning

Material: slides

Iain Murray: Probabilistic Modeling

Material: slides

Amr Ahmed: Big Data and Large Scale Inference

Material: slides (part 1), slides (part 2)

Jean-Philippe Vert: Kernel Methods and Computational Biology

Material: slides

Michael Betancourt: Hamiltonian Monte Carlo and Stan

Material: slides (HMC), slides (Stan)

Frank Wood: Probabilistic Programming and Bayesian Nonparametrics

Material: slides

Ralf Herbrich: Applications of Large Scale Graphical Models

Material: slides, video, and code

Jeff A. Bilmes: Submodularity and Optimization

Material: slides

Mark Girolami: Advanced Topics in Markov Chain Monte Carlo

Material: slides (part 1), slides (part 2)

Chris Holmes: Robust Inference

Material: slides

Timo Koski: Theoretical Issues in Statistical Learning

Material: slides