Playlist: 21 videos

Adversarial Approaches in Machine Learning

0:57:15

Computationally Efficient Alternatives to Nonconvex-Nonconcave Min-Max Optimization

Nisheeth Vishnoi (Yale University)
https://simons.berkeley.edu/talks/computationally-efficient-alternatives-nonconvex-nonconcave-min-max-optimization
Adversarial Approaches in Machine Learning
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0:53:56

Halpern Iteration and Equilibria Problems

Jelena Diakonikolas (University of Wisconsin-Madison)
https://simons.berkeley.edu/talks/tbd-362
Adversarial Approaches in Machine Learning
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0:54:45

Zeroth-Order Methods for Convex-Concave Minmax Problems: Learning from Strategically Generated Data

Chinmay Maheshwari (UC Berkeley)
https://simons.berkeley.edu/talks/tbd-363
Adversarial Approaches in Machine Learning
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0:50:30

Are Single-Loop Algorithms Sufficient for Unbalanced Minimax Optimization？

Niao He (ETH Zürich)
https://simons.berkeley.edu/talks/tbd-364
Adversarial Approaches in Machine Learning
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0:44:41

Policy Gradient: Optimal Estimation, Convergence, and Generalization beyond Cumulative Rewards

Mengdi Wang (Princeton University)
https://simons.berkeley.edu/talks/tbd-365
Adversarial Approaches in Machine Learning
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0:55:50

Of Moments and Matching: Trade-offs and Treatments in Imitation Learning

Steven Wu (Carnegie Mellon University)
https://simons.berkeley.edu/talks/moments-and-matching-trade-offs-and-treatments-imitation-learning
Adversarial Approaches in Machine Learning
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0:53:51

Learning Uninformative Representations

Richard Zemel (Columbia University)
https://simons.berkeley.edu/talks/learning-uninformative-representations
Adversarial Approaches in Machine Learning
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0:49:21

Generalized Energy-Based Models

Arthur Gretton (UCL)
https://simons.berkeley.edu/talks/generalized-energy-based-models
Adversarial Approaches in Machine Learning
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0:47:0

Rebel: Combining Deep Reinforcement Learning and Search for Imperfect-Information Games

Noam Brown (Facebook AI Research)
https://simons.berkeley.edu/talks/rebel-combining-deep-reinforcement-learning-and-search-imperfect-information-games
Adversarial Approaches in Machine Learning
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0:48:11

Online Adversarial Multicalibration And (Multi)Calibeating

Aaron Roth (University of Pennsylvania)
https://simons.berkeley.edu/talks/online-adversarial-multicalibration-and-multicalibeating
Adversarial Approaches in Machine Learning
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