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...

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0:42:44

Representation Learning of Grounded Language and Knowledge: with and without End-to-End Learning

Yejin Choi, University of Washington
Representation Learning
https://simons.berkeley.edu/talks/yejin-choi-2017-3-30
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1:9:16

Representation Learning of Grounded Language and Knowledge: with and without End-to-End Learning

Yann LeCun, New York University
Representation Learning
https://simons.berkeley.edu/talks/yann-lecun-2017-3-30
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0:41:32

Provably Learning of Noisy-or Networks

Rong Ge, Duke University
Representation Learning
https://simons.berkeley.edu/talks/rong-ge-2017-3-30
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0:39:44

Learning Paraphrastic Representations of Natural Language Sentences

Kevin Gimpel, TTI Chicago
Representation Learning
https://simons.berkeley.edu/talks/kevin-gimpel-2017-3-31
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0:43:17

Formation and Association of Symbolic Memories in the Brain

Christos Papadimitriou, UC Berkeley
Representation Learning
https://simons.berkeley.edu/talks/christos-papadimitriou-2017-3-31
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1:6:38

Learning Representations for Active Vision

Bruno Olshausen, UC Berkeley
Representation Learning
https://simons.berkeley.edu/talks/bruno-olshausen-2017-3-31
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0:42:18

Resilient Representation and Provable Generalization

Dawn Song, UC Berkeley
Representation Learning
https://simons.berkeley.edu/talks/dawn-song-2017-03-31
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0:47:18

Word Representation Learning without <unk> Assumptions

Chris Dyer, Carnegie Mellon University
Representation Learning
https://simons.berkeley.edu/talks/chris-dyer-2017-3-31
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