Playlist: 30 videos

Representation Learning

This workshop will focus on dramatic advances in representation and learning taking place in natural language processing, speech and vision. For instance, deep learning can be thought of as a method that combines the tasks of finding a classifier...

0:49:19

Geometry, Optimization and Generalization in Multilayer Networks

Nathan Srebro, TTI Chicago
Representation Learning
https://simons.berkeley.edu/talks/nathan-srebro-bartom-2017-3-27
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0:36:0

A Non-generative Framework and Convex Relaxations for Unsupervised Learning

Elad Hazan, Princeton University
Representation Learning
https://simons.berkeley.edu/talks/elad-hazan-2017-3-27
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1:14:6

Representations for Language: From Word Embeddings to Sentence Meanings

Christopher Manning, Stanford University
Representation Learning
https://simons.berkeley.edu/talks/christopher-manning-2017-3-27
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0:59:31

The Missing Signal

Leon Bottou, Facebook AI Research
Representation Learning
https://simons.berkeley.edu/talks/missing-signal
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0:42:54

Representations of Relationships in Images and Text

Hal Daume, University of Maryland at College Park
Representation Learning
https://simons.berkeley.edu/talks/hal-daume-2017-3-27
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0:17:44

Spotlight Talk: A Formalization of Representation Learning

Andrej Risteski, Princeton University
Representation Learning
https://simons.berkeley.edu/talks/andrej-risteski-2017-03-27
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0:18:30

Spotlight Talk: Semi-Random Units for Learning Neural Networks with Guarantees

Bo Xie, Georgia Institute of Technology
Representation Learning
https://simons.berkeley.edu/talks/bo-xie-2017-03-27
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0:41:44

Unsupervised Discovery Through Adversarial Self-Play

Rob Fergus, New York University
Representation Learning
https://simons.berkeley.edu/talks/rob-fergus-2017-3-28
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0:44:54

Learning from Unlabeled Video

Kristen Grauman, University of Texas, Austin
Representation Learning
https://simons.berkeley.edu/talks/kristen-grauman-2017-3-28
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1:11:34

Deep Reinforcement Learning

Pieter Abbeel, UC Berkeley
Representation Learning
https://simons.berkeley.edu/talks/pieter-abbeel-2017-3-28
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