This are my own summary notes of the MLSS 2018 held at Universidad Autónoma de Madrid, Spain from Aug. 27 to Sep. 7, 2018.
- My draft notes in pdf (Download pdf): These notes may contain wrong information, and should be used only as a reference for further research. The table of contents may be useful to have a brief idea about the full content of the Summer School.
- I do not have currently any clean notes. If I have time, I will try to clean some of the sections and make sure that they do not include wrong information.
The list of speakers and the available material can be found at speakers
The following list contains a copy of the slides downloaded from the aforementioned web site.
- Optimization by Francis Bach slides
- Causal Inference by Joris Mooij slides , exercices
- Gaussian Processes by Richard Turner slides1 , slides2 , slides3
- Bayesian Deep Learning by Shakir Mohamed slides
- Neural Laungauge Models by Kyunghyun Cho slides1 ,slides2 ,slides3 , case1 , case2 , case3
- Bayesian Optimization and Probabilistic Numerics by Michael Osborne slides1 ,slides2 ,slides3
- Generative Adversarial Networks by Sebastian Nowozin slides1
- Machine Learning and Causal Inference for Decision Support by Suchi Saria slides
- Kernel Methods by Arthur Gretton slides1 ,slides2 ,slides3
