:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Lei, Qi, Nagarajan, Sai Ganesh, Panageas, Ioannis, Wang, Xiao
Format:	Preprint
Published:	2020
Subjects:	Machine Learning Computer Science and Game Theory
Online Access:	https://arxiv.org/abs/2002.06768
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Last-iterate Convergence Separation between Extra-gradient and Optimism in Constrained Periodic Games
by: Feng, Yi, et al.
Published: (2024)

Last-Iterate Convergence: Zero-Sum Games and Constrained Min-Max Optimization
by: Daskalakis, Constantinos, et al.
Published: (2018)

Global Convergence of Multi-Agent Policy Gradient in Markov Potential Games
by: Leonardos, Stefanos, et al.
Published: (2021)

Efficient Uncoupled Learning Dynamics with $\tilde{O}\!\left(T^{-1/4}\right)$ Last-Iterate Convergence in Bilinear Saddle-Point Problems over Convex Sets under Bandit Feedback
by: Maiti, Arnab, et al.
Published: (2026)

Convex Markov Games and Beyond: New Proof of Existence, Characterization and Learning Algorithms for Nash Equilibria
by: Barakat, Anas, et al.
Published: (2026)

The Complexity of Two-Team Polymatrix Games with Independent Adversaries
by: Hollender, Alexandros, et al.
Published: (2024)

Learning Equilibria in Adversarial Team Markov Games: A Nonconvex-Hidden-Concave Min-Max Optimization Problem
by: Kalogiannis, Fivos, et al.
Published: (2024)

(Doubly) Exponential Lower Bounds for Follow the Regularized Leader in Potential Games
by: Anagnostides, Ioannis, et al.
Published: (2026)

Strategizing against No-regret Learners
by: Deng, Yuan, et al.
Published: (2019)

Convergence of Regret Matching in Potential Games and Constrained Optimization
by: Anagnostides, Ioannis, et al.
Published: (2025)

No-regret incentive-compatible online learning under exact truthfulness with non-myopic experts
by: Komiyama, Junpei, et al.
Published: (2025)

The Complexity of Symmetric Equilibria in Min-Max Optimization and Team Zero-Sum Games
by: Anagnostides, Ioannis, et al.
Published: (2025)

Efficient Last-iterate Convergence Algorithms in Solving Games
by: Meng, Linjian, et al.
Published: (2023)

Convergence to Nash Equilibrium and No-regret Guarantee in (Markov) Potential Games
by: Dong, Jing, et al.
Published: (2024)

On the price of exact truthfulness in incentive-compatible online learning with bandit feedback: A regret lower bound for WSU-UX
by: Mortazavi, Ali, et al.
Published: (2024)

Responding to Promises: No-regret learning against followers with memory
by: Hebbar, Vijeth, et al.
Published: (2024)

Polynomial Convergence of Bandit No-Regret Dynamics in Congestion Games
by: Dadi, Leello, et al.
Published: (2024)

Efficient Kernelized Learning in Polyhedral Games Beyond Full-Information: From Colonel Blotto to Congestion Games
by: Kontogiannis, Andreas, et al.
Published: (2025)

Computing Nash Equilibria in Potential Games with Private Uncoupled Constraints
by: Patris, Nikolas, et al.
Published: (2024)

Bayes correlated equilibria, no-regret dynamics in Bayesian games, and the price of anarchy
by: Fujii, Kaito
Published: (2023)

Last-iterate Convergence for Symmetric, General-sum, $2 \times 2$ Games Under The Exponential Weights Dynamic
by: Wang, Guanghui, et al.
Published: (2025)

Optimal No-regret Learning in Repeated First-price Auctions
by: Han, Yanjun, et al.
Published: (2020)

Hierarchies of No-regret Algorithms
by: Xu, R., et al.
Published: (2026)

Time-Efficient Algorithms for Nash-Bargaining-Based Matching Market Models
by: Panageas, Ioannis, et al.
Published: (2021)

Last-iterate Convergence in Regularized Graphon Mean Field Game
by: Dong, Jing, et al.
Published: (2024)

An $α$-regret analysis of Adversarial Bilateral Trade
by: Azar, Yossi, et al.
Published: (2022)

Efficient Last-Iterate Convergence in Regret Minimization via Adaptive Reward Transformation
by: Ren, Hang, et al.
Published: (2025)

Algorithms and Complexity for Computing Nash Equilibria in Adversarial Team Games
by: Anagnostides, Ioannis, et al.
Published: (2023)

Last-Iterate Convergence Properties of Regret-Matching Algorithms in Games
by: Cai, Yang, et al.
Published: (2023)

Last-Iterate Convergence of No-Regret Learning for Equilibria in Bargaining Games
by: Kamp, Serafina, et al.
Published: (2025)

The Economics of No-regret Learning Algorithms
by: Hartline, Jason
Published: (2026)

Last-Iterate Convergence of Payoff-Based Independent Learning in Zero-Sum Stochastic Games
by: Chen, Zaiwei, et al.
Published: (2024)

Randomized learning-augmented auctions with revenue guarantees
by: Caragiannis, Ioannis, et al.
Published: (2024)

Regularized Proportional Fairness Mechanism for Resource Allocation Without Money
by: Zeng, Sihan, et al.
Published: (2025)

Performative Prediction with Neural Networks
by: Mofakhami, Mehrnaz, et al.
Published: (2023)

Computational Lower Bounds for Regret Minimization in Normal-Form Games
by: Anagnostides, Ioannis, et al.
Published: (2024)

Barriers to Welfare Maximization with No-Regret Learning
by: Anagnostides, Ioannis, et al.
Published: (2024)

Scale-Invariant Regret Matching and Online Learning with Optimal Convergence: Bridging Theory and Practice in Zero-Sum Games
by: Zhang, Brian Hu, et al.
Published: (2025)

Multiplicative weights, equalizers, and P=PPAD
by: Avramopoulos, Ioannis
Published: (2016)

First-order (coarse) correlated equilibria in non-concave games
by: Ahunbay, Mete Şeref
Published: (2024)