Dynamical Systems and Learning in Games (Part IV)

Channel:
United States Simons Institute for the Theory of Computing
Subscribers:
68,700
Published on ● Video Link: https://www.youtube.com/watch?v=k3FB4xhl2-4


Duration: 1:09:00
499 views
11

Georgios Piliouras (Singapore University of Technology and Design)
https://simons.berkeley.edu/talks/dynamical-systems-and-learning-games-part-iv
Learning and Games Boot Camp



Other Videos By Simons Institute for the Theory of Computing


2022-01-28Prefix Discrepancy, Smoothed Analysis, and Combinatorial Vector Balancing
2022-01-28Mixing of 3-term progressions in Quasirandom Groups
2022-01-28Distributed Vertex Cover Reconfiguration
2022-01-28On Fairness and Stability in Two-Sided Matchings
2022-01-28Learning and Incentives (Part IV)
2022-01-28Learning and Incentives (Part III)
2022-01-28Econometrics in Games and Auctions (Part II)
2022-01-27Econometrics in Games and Auctions (Part I)
2022-01-27Learning and Incentives (Part II)
2022-01-27Learning and Incentives (Part I)
2022-01-27Dynamical Systems and Learning in Games (Part IV)
2022-01-26Dynamical Systems and Learning in Games (Part III)
2022-01-26Dynamical Systems and Learning in Games (Part II)
2022-01-26Dynamical Systems and Learning in Games (Part I)
2022-01-26Min-Max Optimization (Part IV)
2022-01-25Min-Max Optimization (Part III)
2022-01-25Learning as a Solution Concept (Part II)
2022-01-25Learning as a Solution Concept (Part I)
2022-01-25Min-Max Optimization (Part II)
2022-01-24Min-Max Optimization (Part I)
2022-01-22Introduction to Experimental Design


Tags:
Simons Institute
theoretical computer science
UC Berkeley
Computer Science
Theory of Computation
Theory of Computing
Learning and Games Boot Camp
Georgios Piliouras