Exploiting geometric structure in (matrix-valued) optimization

Channel:
United States Simons Institute for the Theory of Computing
Subscribers:
68,700
Published on ● Video Link: https://www.youtube.com/watch?v=DM17pUIlnB0


Duration: 39:59
1,506 views
33

Melanie Weber (Harvard University)
https://simons.berkeley.edu/talks/melanie-weber-harvard-university-2023-11-27
Optimization and Algorithm Design



Other Videos By Simons Institute for the Theory of Computing


2023-12-01Network Unreliability in Sub-quadratic Time
2023-12-01Recent Progress on Submodular Function Minimization
2023-12-01Quotient Sparsification for Submodular Functions
2023-12-01Discrepancy Minimization via Regularization
2023-12-01Breaking the quadratic gap for strongly polynomial solvers to combinatorial linear programs
2023-11-30Sparsifying Generalized Linear Models
2023-11-30Instance Optimal Iterative Methods for Matrix Function Approximation
2023-11-29Nash Social Welfare and A Tale of Mathematical Programs
2023-11-29Robust Gradient Descent: Agnostically Estimating an Unknown Affine Transformation...
2023-11-28Hitting the High-D(imensional) Notes: An ODE for SGD learning dynamics in high-dimensions
2023-11-27Exploiting geometric structure in (matrix-valued) optimization
2023-11-21Towards Interpretable Data Science
2023-11-13Introduction and Program Highlights
2023-11-13Modern Paradigms in Generalization
2023-11-13Challenges in Research on Practical Algorithms
2023-11-13Well-Being, AI, and You
2023-11-13Quantum Algorithms, Complexity, and Fault Tolerance: Sandy Irani
2023-11-13How looking at a problem quantumly could solve it faster?
2023-11-01Streaming (Synchronous), Recursion, and Incremental Computation
2023-10-28Complementarities and Externalities
2023-10-28Stability in Tranding Networks


Tags:
Simons Institute
theoretical computer science
UC Berkeley
Computer Science
Theory of Computation
Theory of Computing
Optimization and Algorithm Design
Melanie Weber