Lectures and Slides

2020 Deep Learning and Reinforcement Learning Summer School

The 2020 CIFAR Deep Learning and Reinforcement Learning Summer School will be hosted by Mila and will take place from July 29 to August 6, 2020 in Montreal, Quebec.

Slides and lectures will be made available after the event.

2019 Deep Learning and Reinforcement Learning Summer School

The 2019 CIFAR Deep Learning and Reinforcement Learning Summer School was hosted by Amii and took place from July 24 to August 2, 2019 in Edmonton, Alberta.

2019 Video Lectures

2019 Deep Learning and Reinforcement Summer School (DLRLSS) Slides

 

Date Presenter Presentation
Wednesday, July 24 Hugo Larochelle Neural Networks 1
Hugo Larochelle Neural Networks 2
Thursday, July 25 Angel Chang Deep Learning for Images
Yoshua Bengio Recurrent Nets and Attention for System 2 Processing
Friday, July 26 Jörn-Henrik Jacobsen Unsupervised Learning with Autoencoders and Likelihood-based Generative Models
Saturday, July 27 Yoshua Bengio What’s next
Monday, July 29 Adam White TD/RL
Csaba Szepesvari Bandits Algorithms
Tuesday, July 30 Pascal Poupart  POMDPs
Dale Schuurmans Foundations for RL
Wednesday, July 31 Matt Taylor Human in the Loop
Marek Petrik Robust RL
James Wright Multi-agent Systems
Thursday, August 1 JMatteo Hessel Deep RL1
Anna Harutyunyan Deep RL2
Friday, August 2 A. Rupam Mahmood RL with Robots
Rich Sutton RL Research/frontiers

2018 Deep Learning and Reinforcement Learning Summer School

The 2018 CIFAR Deep Learning and Reinforcement Learning Summer School was hosted by the Vector Institute and took place from July 25 to August 3 in Toronto, Ontario.

2018 Video Lectures

2018 DEEP LEARNING SUMMER SCHOOL (DLSS) SLIDES

Date Presenter Presentation
Wednesday, July 25 Katherine Heller Introduction to Machine Learning
Hugo Larochelle Neural Networks I
Thursday, July 26 Hugo Larochelle Neural Networks II
Jonathon Shlens Introduction to CNN’s
Friday, July 27 David Duvenaud Generative Models I
Phil Isola Generative Models II
Been Kim Interpretability
Saturday, July 28 Sanjeev Arora Theory
Jimmy Ba Optimization I
Jorge Nocedal Optimization II
Monday, July 30 Yoshua Bengio RNN’s 
Graham Neubig Language Understanding
Jamie Kiros Multimodel Learning
Tuesday, July 31 Blake Richards Computational Neuroscience
Andrew Wilson Bayesian Neural Nets

2018 REINFORCEMENT LEARNING SUMMER SCHOOL (RLSS) SLIDES

Date Presenter Presentation
Wednesday, August 1 Richard Sutton Introduction to RL and TD
Sergey Levine Policy Search
Amir-Massoud Farahmand Batch RL and ADP
Martha White Off-Policy Learning
Thursday, August 2 Ajay Agrawal Prediction Machines:
The Simple Economics of A
I
Tor Lattimore Bandits and Explore/Exploit in RL
Doina Precup Temporal Abstraction
Emma Brunskill Multi-task and Transfer in RL
Friday, August 3 Marc Belleare Deep RL
Hal Daume III Imitation Learning
Mohammad Ghavamzadeh Safety in RL
Michael Bowling Multi-agent RL
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