Deep Learning and Reinforcement Learning Summer School, Toronto 2018

Deep Learning and Reinforcement Learning Summer School, Toronto 2018

29 Lectures · Jul 24, 2018

About

Deep neural networks are a powerful method for automatically learning distributed representations at multiple levels of abstraction. Over the past decade, they have dramatically pushed forward the state-of-the-art in domains as diverse as vision, language understanding, robotics, game playing, graphics, health care, and genomics. The Deep Learning Summer School (DLSS) covers both the foundations and applications of deep neural networks, from fundamental concepts to cutting-edge research results.

The Reinforcement Learning Summer School (RLSS) covers the basics of reinforcement learning and show its most recent research trends and discoveries, as well as present an opportunity to interact with graduate students and senior researchers in the field.

The 2018 DLSS and the RLSS are hosted by the Canadian Institute For Advanced Research (CIFAR) and the Vector Institute, with participation and support from the Alberta Machine Intelligence Institute and the Institut québécois d’intelligence artificielle (MILA).

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Deep Learning Summer School

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01:24:37

Introduction to Machine Learning

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Neural Networks I

Hugo Larochelle

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Autodiff

David Kristjanson Duvenaud

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Neural Networks II

Hugo Larochelle

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2169 Views

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Advanced Deep Vision

Sanja Fidler

Oct 11, 2018

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RAMP (Practical session)

Balázs Kégl

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1386 Views

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01:29:36

Generative Models I

David Kristjanson Duvenaud

Oct 11, 2018

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3258 Views

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01:21:23

Generative Models II

Phillip Isola

Oct 11, 2018

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1845 Views

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01:19:01

Interpretability

Been Kim

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2837 Views

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Theory

Sanjeev Arora

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01:09:46

Optimization I

Jimmy Ba

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2956 Views

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Optimization II

Jorge Nocedal

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1600 Views

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Recurrent Neural Networks (RNNs)

Yoshua Bengio

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5046 Views

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01:26:03

Language Understanding

Graham Neubig

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1780 Views

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Multimodal Learning

Jamie Kiros

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Computational Neuroscience

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Bayesian Neural Nets

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Deep Learning and Music

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Reinforcement Learning Summer School

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Introduction to RL and TD

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7618 Views

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Policy Search

Sergey Levine

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Batch RL and ADP

Amir-massoud Farahmand

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01:22:11

Off-Policy Learning

Martha White

Oct 19, 2018

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Bandits and Explore/Exploit in RL

Tor Lattimore

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01:31:48

Temporal Abstraction

Doina Precup

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01:26:17

Multi-task and Transfer in RL

Emma Brunskill

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1354 Views

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Deep RL

Marc G. Bellemare

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Imitation Learning

Hal Daumé III

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1408 Views

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Safety in RL

Mohammad Ghavamzadeh

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1311 Views

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Multi-agent RL

Michael Bowling

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1921 Views

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