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Deep Learning and Reinforcement Learning Summer School, Toronto 2018

Deep Learning and Reinforcement Learning Summer School, Toronto 2018

30 Videos · 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).

Videos

Deep Learning Summer School

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01:24:15

Optimization II

Jorge Nocedal

calendar icon Oct 11, 2018 1640 views

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01:24:37

Introduction to Machine Learning

Katherine A. Heller

calendar icon Oct 11, 2018 18087 views

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01:28:29

Neural Networks I

Hugo Larochelle

calendar icon Oct 11, 2018 6025 views

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01:33:51

Neural Networks II

Hugo Larochelle

calendar icon Oct 11, 2018 2197 views

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01:28:58

Deep Learning and Music

Sageev Oore

calendar icon Oct 11, 2018 1513 views

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01:33:54

Advanced Deep Vision

Sanja Fidler

calendar icon Oct 11, 2018 3869 views

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01:09:46

Optimization I

Jimmy Ba

calendar icon Oct 11, 2018 3012 views

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01:30:39

Recurrent Neural Networks (RNNs)

Yoshua Bengio

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01:18:45

RAMP (Practical session)

Balázs Kégl

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Draft
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01:18:27

Introduction to Convolutional Neural Networks (CNNs)

Jonathon Shlens

calendar icon Oct 11, 2018 2513 views

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01:34:52

Computational Neuroscience

Blake Aaron Richards

calendar icon Oct 11, 2018 1775 views

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01:31:39

Bayesian Neural Nets

Andrew Gordon Wilson

calendar icon Oct 11, 2018 7427 views

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01:19:01

Interpretability

Been Kim

calendar icon Oct 11, 2018 2858 views

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01:19:43

Multimodal Learning

Jamie Kiros

calendar icon Oct 11, 2018 1910 views

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01:26:03

Language Understanding

Graham Neubig

calendar icon Oct 11, 2018 1812 views

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01:21:23

Generative Models II

Phillip Isola

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01:29:36

Generative Models I

David Kristjanson Duvenaud

calendar icon Oct 11, 2018 3307 views

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01:30:51

Theory

Sanjeev Arora

calendar icon Oct 11, 2018 2006 views

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01:17:56

Autodiff

David Kristjanson Duvenaud

calendar icon Oct 11, 2018 2760 views

Reinforcement Learning Summer School

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01:29:34

Policy Search

Sergey Levine

calendar icon Oct 11, 2018 2708 views

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01:31:48

Temporal Abstraction

Doina Precup

calendar icon Oct 11, 2018 1574 views

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01:20:53

Bandits and Explore/Exploit in RL

Tor Lattimore

calendar icon Oct 11, 2018 1290 views

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01:26:17

Multi-task and Transfer in RL

Emma Brunskill

calendar icon Oct 11, 2018 1404 views

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01:01:37

Multi-agent RL

Michael Bowling

calendar icon Oct 11, 2018 1951 views

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01:26:23

Deep RL

Marc G. Bellemare

calendar icon Oct 11, 2018 1677 views

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01:00:27

Safety in RL

Mohammad Ghavamzadeh

calendar icon Oct 11, 2018 1342 views

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01:05:05

Imitation Learning

Hal Daumé III

calendar icon Oct 11, 2018 1451 views

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01:22:11

Off-Policy Learning

Martha White

calendar icon Oct 19, 2018 2126 views

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01:28:53

Introduction to RL and TD

Richard S. Sutton

calendar icon Oct 11, 2018 7722 views

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01:31:51

Batch RL and ADP

Amir-massoud Farahmand

calendar icon Oct 11, 2018 1688 views

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