Deep Learning Summer School (DLSS)

 

Saturday, July 28
Theory
Sanjeev Arora

Optimization I
Jimmy Ba

Optimization II
Jorge Nocedal

 

Monday, July 30

RNN’s 
Yoshua Bengio

Language Understanding
Graham Neubig

Multimodel Learning
Jamie Kiros

 

Tuesday, July 31

Computational Neuroscience
Blake Richards

Bayesian Neural Nets
Andrew Wilson

 

 

Wednesday, July 25
Introduction to Machine Learning
Katherine Heller

Neural Networks I
Hugo Larochelle 

 

Thursday, July 26

Neural Networks II
Hugo Larochelle

Introduction to CNN’s
Jonathon Shlens

 

 

Friday, July 27

Generative Models I
David Duvenaud

Generative Models II
Phil Isola

Interpretability 
Been Kim

 

 

Reinforcement Learning Summer School (RLSS)

 

Wednesday, August 1

Introduction to RL and TD
Richard Sutton

Policy Search
Sergey Levine

Batch RL and ADP
Amir-Massoud Farahmand

Off-Policy Learning
Martha White

 

Thursday, August 2

Prediction Machines: The Simple Economics of Artificial Intelligence
Ajay Agrawal

Bandits and Explore/Exploit in RL
Tor Lattimore

Temporal Abstraction
Doina Precup

Multi-task and Transfer in RL
Emma Brunskill

 

Friday, August 3

Deep RL
Marc Belleare

Imitation Learning
Hal Daume III

Safety in RL
Mohammad Ghavamzadeh

Multi-agent RL
Michael Bowling

 

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