conftrace_

multiplicative weights update

18 papers

Explore in graph

Also known as

MWU

Co-occurring keywords

nash equilibrium (398) game theory (854) zero-sum game (190) dynamical system (398) last-iterate convergence (20) lyapunov chao (2) regret minimization (315) online learning (1777) nonconvex optimization (316) noisy gradient (5)

Papers

Langevin Multiplicative Weights Update with Applications in Polynomial Portfolio Management AAAI 2025
Fast Last-Iterate Convergence of Learning in Games Requires Forgetful Algorithms NIPS 2024
Robust Load Balancing with Machine Learned Advice JMLR 2023
Last-Iterate Convergence with Full and Noisy Feedback in Two-Player Zero-Sum Games AISTATS 2023
Forward Looking Best-Response Multiplicative Weights Update Methods for Bilinear Zero-sum Games AISTATS 2022
Consensus Multiplicative Weights Update: Learning to Learn using Projector-based Game Signatures ICML 2022
Accelerated Multiplicative Weights Update Avoids Saddle Points Almost Always IJCAI 2022
Scalable and Memory-Efficient Algorithms for Controlling Networked Epidemic Processes Using Multiplicative Weights Update Method IJCAI 2022
Learning in Matrix Games can be Arbitrarily Complex COLT 2021
Online k-means Clustering AISTATS 2021
Near-Optimal No-Regret Learning in General Games NIPS 2021
Chaos, Extremism and Optimism: Volume Analysis of Learning in Games NIPS 2020
Robust and Heavy-Tailed Mean Estimation Made Simple, via Regret Minimization NIPS 2020
The route to chaos in routing games: When is price of anarchy too optimistic? NIPS 2020
Rethinking Generative Mode Coverage: A Pointwise Guaranteed Approach NIPS 2019
Multiplicative Weights Updates as a distributed constrained optimization algorithm: Convergence to second-order stationary points almost always ICML 2019
Vortices Instead of Equilibria in MinMax Optimization: Chaos and Butterfly Effects of Online Learning in Zero-Sum Games COLT 2019
Randomized Strategies for Robust Combinatorial Optimization AAAI 2019