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08/22/2023
EM for Mixture of Linear Regression with Clustered Data
Modern data-driven and distributed learning frameworks deal with diverse...
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07/13/2023
Multi-Player Zero-Sum Markov Games with Networked Separable Interactions
We study a new class of Markov games (MGs), Multi-player Zero-sum Markov...
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03/03/2023
A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games
We study two-player zero-sum stochastic games, and propose a form of ind...
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12/28/2022
Revisiting the Linear-Programming Framework for Offline RL with General Function Approximation
Offline reinforcement learning (RL) concerns pursuing an optimal policy ...
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10/23/2022
Symmetric (Optimistic) Natural Policy Gradient for Multi-agent Learning with Parameter Convergence
Multi-agent interactions are increasingly important in the context of re...
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06/19/2022
The Power of Regularization in Solving Extensive-Form Games
In this paper, we investigate the power of regularization, a common tech...
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06/12/2022
Convergence and Stability of Coupled Belief–Strategy Learning Dynamics in Continuous Games
We propose a learning dynamics to model how strategic agents repeatedly ...
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06/09/2022
What is a Good Metric to Study Generalization of Minimax Learners?
Minimax optimization has served as the backbone of many machine learning...
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05/23/2022
Fictitious Play in Markov Games with Single Controller
Certain but important classes of strategic-form games, including zero-su...
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01/10/2022
Optimal and Differentially Private Data Acquisition: Central and Local Mechanisms
We consider a platform's problem of collecting data from privacy sensiti...
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11/23/2021
Independent Learning in Stochastic Games
Reinforcement learning (RL) has recently achieved tremendous successes i...
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09/02/2021
Multi-agent Bayesian Learning with Best Response Dynamics: Convergence and Stability
We study learning dynamics induced by strategic agents who repeatedly pl...
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06/04/2021
Decentralized Q-Learning in Zero-sum Markov Games
We study multi-agent reinforcement learning (MARL) in infinite-horizon d...
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02/16/2021
Optimal intervention in traffic networks
We present an efficient algorithm to identify which edge should be impro...
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02/07/2021
Generalization of Model-Agnostic Meta-Learning Algorithms: Recurring and Unseen Tasks
In this paper, we study the generalization properties of Model-Agnostic ...
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10/18/2020
Multi-agent Bayesian Learning with Adaptive Strategies: Convergence and Stability
We study learning dynamics induced by strategic agents who repeatedly pl...
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10/08/2020
Fictitious play in zero-sum stochastic games
We present fictitious play dynamics for the general class of stochastic ...
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02/21/2020
GANs May Have No Nash Equilibria
Generative adversarial networks (GANs) represent a zero-sum game between...
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02/19/2020
Personalized Federated Learning: A Meta-Learning Approach
The goal of federated learning is to design algorithms in which several ...
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02/13/2020
An Optimal Multistage Stochastic Gradient Method for Minimax Problems
In this paper, we study the minimax optimization problem in the smooth a...
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02/12/2020
Provably Convergent Policy Gradient Methods for Model-Agnostic Meta-Reinforcement Learning
We consider Model-Agnostic Meta-Learning (MAML) methods for Reinforcemen...
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01/31/2020
Last Iterate is Slower than Averaged Iterate in Smooth Convex-Concave Saddle Point Problems
In this paper we study the smooth convex-concave saddle point problem. S...
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01/09/2020
Optimal dynamic information provision in traffic routing
We consider a two-road dynamic routing game where the state of one of th...
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10/31/2019
A Decentralized Proximal Point-type Method for Saddle Point Problems
In this paper, we focus on solving a class of constrained non-convex non...
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08/27/2019
On the Convergence Theory of Gradient-Based Model-Agnostic Meta-Learning Algorithms
In this paper, we study the convergence theory of a class of gradient-ba...
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06/03/2019
Proximal Point Approximations Achieving a Convergence Rate of O(1/k) for Smooth Convex-Concave Saddle Point Problems: Optimistic Gradient and Extra-gradient Methods
In this paper we analyze the iteration complexity of the optimistic grad...
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01/24/2019
A Unified Analysis of Extra-gradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point Approach
We consider solving convex-concave saddle point problems. We focus on tw...
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01/23/2019
A Universally Optimal Multistage Accelerated Stochastic Gradient Method
We study the problem of minimizing a strongly convex and smooth function...
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09/06/2018
Escaping Saddle Points in Constrained Optimization
In this paper, we focus on escaping from saddle points in smooth nonconv...
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07/12/2018
Convergence Rate of Block-Coordinate Maximization Burer-Monteiro Method for Solving Large SDPs
Semidefinite programming (SDP) with equality constraints arise in many o...
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01/31/2018
Graphon games
The study of strategic behavior in large scale networks via standard gam...
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12/22/2017
A variational inequality framework for network games: Existence, uniqueness, convergence and sensitivity analysis
We provide a unified variational inequality framework for the study of f...
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10/08/2012