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

Published on ● Video Link: https://www.youtube.com/watch?v=7Zzg_TQgAbg



Duration: 42:44
3,787 views
58


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




Other Videos By Simons Institute for the Theory of Computing


2017-04-04In Pursuit of Structure: Why a Little Randomness (Almost) Always Helps
2017-03-31Spotlght Talk: Performance Guarantees for Transferring Representations
2017-03-31Word Representation Learning without unk Assumptions
2017-03-31Resilient Representation and Provable Generalization
2017-03-31Learning Representations for Active Vision
2017-03-31Formation and Association of Symbolic Memories in the Brain
2017-03-31Learning Paraphrastic Representations of Natural Language Sentences
2017-03-30Provably Learning of Noisy-or Networks
2017-03-30Unsupervised Representation Learning
2017-03-30Generalization and Equilibrium in Generative Adversarial Nets (GANs)
2017-03-30Representation Learning of Grounded Language and Knowledge: with and without End-to-End Learning
2017-03-30Re-Thinking Representational Learning in Robotics and Music
2017-03-29Spotlight Talk: How to Escape Saddle Points Efficiently
2017-03-29Tractable Learning in Structured Probability Spaces
2017-03-29Spotlight Talk: Convolutional Dictionary Learning through Tensor Factorization
2017-03-29Representation Learning for Reading Comprehension
2017-03-29Evaluating Neural Network Representations Against Human Cognition
2017-03-29Adversarial Perceptual Representation Learning Across Diverse Modalities and Domains
2017-03-29Continuous State Machines and Grammars for Linguistic Structure Prediction
2017-03-28Failures of Deep Learning
2017-03-28Supersizing Self-Supervision: Learning Perception and Action without Human Supervision



Tags:
Yejin Choi
Simons Institute
Theory of Computing
Theory of Computation
Theoretical Computer Science
Computer Science
UC Berkeley
Representation Learning