Uniform Convergence Rates for Lipschitz Learning Down to Graph Connectivity

Uniform Convergence Rates for Lipschitz Learning Down to Graph Connectivity

Channel:
United States Simons Institute for the Theory of Computing
Subscribers:
69,000
Published on ● Video Link: https://www.youtube.com/watch?v=UGU_f9U_M28


Duration: 55:36
327 views
7

Jeff Calder (University of Minnesota)
https://simons.berkeley.edu/talks/uniform-convergence-rates
Dynamics and Discretization: PDEs, Sampling, and Optimization



Other Videos By Simons Institute for the Theory of Computing


2021-10-29Consensus Based Sampling
2021-10-29Continuous Time Stochastic Gradient Descent and Flat Minimum Selection
2021-10-29Mean-Field Theory of Two-Layers Neural Networks: Dimension Free Bounds and Example
2021-10-28Archetypal Analysis
2021-10-28Linearised Optimal Transport Distances
2021-10-28Wasserstein GANs Work Because They Fail (to Approximate the Wasserstein Distance)
2021-10-28Global Well Posedness of Master Equations Mean Field Games
2021-10-27The Singular Set in the Stefan Problem
2021-10-27Optimal Transport With Stopping Times and the Stefan Problem
2021-10-27Foundations of Computing: Donald Knuth | Polylogues
2021-10-27Uniform Convergence Rates for Lipschitz Learning Down to Graph Connectivity
2021-10-27Hessian Informed Mirror Descent With Application in Gradient Flows
2021-10-27Optimal Transport for Learning Chaotic Dynamics via Invariant Measures
2021-10-27Panel on Bosonic Error Correction Codes | Quantum Colloquium
2021-10-27An Error-Corrected Logical Quantum Bit Encoded in Grid States of a Superconducting Cavity
2021-10-27Sampling via Birth-Death Dynamics
2021-10-26Dissipative Evolution of Probability Measures
2021-10-26An Optimal Transport Problem With Bulk/Interface Interactions
2021-10-26A Duality Approach for Entropic-Regularized Optimal Transport: ...
2021-10-26Training Wasserstein Generative Adversarial Networks Without Gradient Penalties
2021-10-26The Most Likely Evolution of Diffusing and Vanishing Particles in the Spirit of E. Schroedinger:..


Tags:
Simons Institute
theoretical computer science
UC Berkeley
Computer Science
Theory of Computation
Theory of Computing
Dynamics and Discretization: PDEs Sampling and Optimization
Jeff Calder