(Hidden) Symmetries of Computational Problems (continued)

(Hidden) Symmetries of Computational Problems (continued)

Channel:
United States Simons Institute for the Theory of Computing
Subscribers:
68,700
Published on ● Video Link: https://www.youtube.com/watch?v=SuYAzwzEgQ8


Duration: 1:11:10
566 views
8

Avi Wigderson (IAS School of Mathematics) & Michael Walter (University of Amsterdam & QuSoft)
https://simons.berkeley.edu/talks/tbd-336
Geometric Methods in Optimization and Sampling Boot Camp



Other Videos By Simons Institute for the Theory of Computing


2021-09-13Approximating Distributions Using Well-Conditioned Normalizing Flows
2021-09-13Iterative Methods and High-Dimensional Statistics
2021-09-13Geometric Methods for Machine Learning and Optimization
2021-09-13Optimal Transport for Inverse Problems
2021-09-13Graphical Optimal Transport and Its Applications
2021-09-13Modularity and Edge-Sampling
2021-09-13The Seeds of Stories
2021-09-13Linear Predictors in Reinforcement Learning: ...
2021-09-04Optimization and Sampling Under Symmetry: Part 2 -- Lie Theory
2021-09-04Optimization and Sampling Under Symmetry: Part 1 -- Examples
2021-09-04(Hidden) Symmetries of Computational Problems (continued)
2021-09-03(Hidden) Symmetries of Computational Problems
2021-09-03PDE on Graphs and Their Continuum Limits
2021-09-03Consensus-Based Interacting Particle Systems and Mean-field PDEs for Optimization and Sampling
2021-09-03Optimal Transport and PDE: Gradient Flows in the Wasserstein Metric (continued)
2021-09-02Optimal Transport and PDE: Gradient Flows in the Wasserstein Metric
2021-09-02Gradient Flows and Optimal Transport in Discrete and Quantum Systems
2021-09-02Computational Optimal Transport
2021-09-02Crash Course on Optimal Transport (continued)
2021-09-01Crash Course on Optimal Transport
2021-09-01An Introduction to Hamiltonian Monte Carlo Method for Sampling


Tags:
Simons Institute
theoretical computer science
UC Berkeley
Computer Science
Theory of Computation
Theory of Computing
Geometric Methods in Optimization and Sampling Boot Camp
Avi Wigderson
Michael Walter