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

Oct 11, 2018

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1622 views

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01:24:37

Introduction to Machine Learning

Katherine A. Heller

Oct 11, 2018

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18050 views

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01:28:29

Neural Networks I

Hugo Larochelle

Oct 11, 2018

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5996 views

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01:33:51

Neural Networks II

Hugo Larochelle

Oct 11, 2018

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2190 views

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01:28:58

Deep Learning and Music

Sageev Oore

Oct 11, 2018

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1501 views

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01:33:54

Advanced Deep Vision

Sanja Fidler

Oct 11, 2018

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3862 views

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01:09:46

Optimization I

Jimmy Ba

Oct 11, 2018

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3000 views

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01:30:39

Recurrent Neural Networks (RNNs)

Yoshua Bengio

Oct 11, 2018

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5105 views

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01:18:45

RAMP (Practical session)

Balázs Kégl

Oct 11, 2018

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1417 views

Draft
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01:18:27

Introduction to Convolutional Neural Networks (CNNs)

Jonathon Shlens

Oct 11, 2018

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2513 views

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01:34:52

Computational Neuroscience

Blake Aaron Richards

Oct 11, 2018

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1759 views

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01:31:39

Bayesian Neural Nets

Andrew Gordon Wilson

Oct 11, 2018

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7409 views

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01:19:01

Interpretability

Been Kim

Oct 11, 2018

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2852 views

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01:19:43

Multimodal Learning

Jamie Kiros

Oct 11, 2018

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1902 views

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01:26:03

Language Understanding

Graham Neubig

Oct 11, 2018

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1804 views

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01:21:23

Generative Models II

Phillip Isola

Oct 11, 2018

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1863 views

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01:29:36

Generative Models I

David Kristjanson Duvenaud

Oct 11, 2018

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3290 views

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01:30:51

Theory

Sanjeev Arora

Oct 11, 2018

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1998 views

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01:17:56

Autodiff

David Kristjanson Duvenaud

Oct 11, 2018

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2747 views

Reinforcement Learning Summer School

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01:29:34

Policy Search

Sergey Levine

Oct 11, 2018

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2684 views

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01:31:48

Temporal Abstraction

Doina Precup

Oct 11, 2018

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1559 views

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01:20:53

Bandits and Explore/Exploit in RL

Tor Lattimore

Oct 11, 2018

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1276 views

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01:26:17

Multi-task and Transfer in RL

Emma Brunskill

Oct 11, 2018

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1393 views

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01:01:37

Multi-agent RL

Michael Bowling

Oct 11, 2018

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1937 views

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01:26:23

Deep RL

Marc G. Bellemare

Oct 11, 2018

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1668 views

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01:00:27

Safety in RL

Mohammad Ghavamzadeh

Oct 11, 2018

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1333 views

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01:05:05

Imitation Learning

Hal Daumé III

Oct 11, 2018

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1434 views

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01:22:11

Off-Policy Learning

Martha White

Oct 19, 2018

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2106 views

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01:28:53

Introduction to RL and TD

Richard S. Sutton

Oct 11, 2018

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7678 views

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01:31:51

Batch RL and ADP

Amir-massoud Farahmand

Oct 11, 2018

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1678 views