Asuman Ozdaglar

research

∙ 08/22/2023

EM for Mixture of Linear Regression with Clustered Data

Modern data-driven and distributed learning frameworks deal with diverse...

0 Amirhossein Reisizadeh, et al. ∙

research

∙ 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...

0 Chanwoo Park, et al. ∙

research

∙ 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...

0 Zaiwei Chen, et al. ∙

research

∙ 12/28/2022

Revisiting the Linear-Programming Framework for Offline RL with General Function Approximation

Offline reinforcement learning (RL) concerns pursuing an optimal policy ...

0 Asuman Ozdaglar, et al. ∙

research

∙ 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...

0 Sarath Pattathil, et al. ∙

research

∙ 06/19/2022

The Power of Regularization in Solving Extensive-Form Games

In this paper, we investigate the power of regularization, a common tech...

0 Mingyang Liu, et al. ∙

research

∙ 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 ...

0 Manxi Wu, et al. ∙

research

∙ 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...

0 Asuman Ozdaglar, et al. ∙

research

∙ 05/23/2022

Fictitious Play in Markov Games with Single Controller

Certain but important classes of strategic-form games, including zero-su...

0 Muhammed O. Sayin, et al. ∙

research

∙ 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...

0 Alireza Fallah, et al. ∙

research

∙ 11/23/2021

Independent Learning in Stochastic Games

Reinforcement learning (RL) has recently achieved tremendous successes i...

0 Asuman Ozdaglar, et al. ∙

research

∙ 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...

0 Manxi Wu, et al. ∙

research

∙ 06/04/2021

Decentralized Q-Learning in Zero-sum Markov Games

We study multi-agent reinforcement learning (MARL) in infinite-horizon d...

0 Muhammed O. Sayin, et al. ∙

research

∙ 02/16/2021

Optimal intervention in traffic networks

We present an efficient algorithm to identify which edge should be impro...

0 Leonardo Cianfanelli, et al. ∙

research

∙ 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 ...

0 Alireza Fallah, et al. ∙

research

∙ 10/18/2020

Multi-agent Bayesian Learning with Adaptive Strategies: Convergence and Stability

We study learning dynamics induced by strategic agents who repeatedly pl...

0 Manxi Wu, et al. ∙

research

∙ 10/08/2020

Fictitious play in zero-sum stochastic games

We present fictitious play dynamics for the general class of stochastic ...

0 Muhammed O. Sayin, et al. ∙

research

∙ 02/21/2020

GANs May Have No Nash Equilibria

Generative adversarial networks (GANs) represent a zero-sum game between...

0 Farzan Farnia, et al. ∙

research

∙ 02/19/2020

Personalized Federated Learning: A Meta-Learning Approach

The goal of federated learning is to design algorithms in which several ...

4 Alireza Fallah, et al. ∙

research

∙ 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...

0 Alireza Fallah, et al. ∙

research

∙ 02/12/2020

Provably Convergent Policy Gradient Methods for Model-Agnostic Meta-Reinforcement Learning

We consider Model-Agnostic Meta-Learning (MAML) methods for Reinforcemen...

1 Alireza Fallah, et al. ∙

research

∙ 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...

0 Noah Golowich, et al. ∙

research

∙ 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...

0 Emily Meigs, et al. ∙

research

∙ 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...

0 Weijie Liu, et al. ∙

research

∙ 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...

0 Alireza Fallah, et al. ∙

research

∙ 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...

0 Aryan Mokhtari, et al. ∙

research

∙ 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...

0 Aryan Mokhtari, et al. ∙

research

∙ 01/23/2019

A Universally Optimal Multistage Accelerated Stochastic Gradient Method

We study the problem of minimizing a strongly convex and smooth function...

0 Necdet Serhat Aybat, et al. ∙

research

∙ 09/06/2018

Escaping Saddle Points in Constrained Optimization

In this paper, we focus on escaping from saddle points in smooth nonconv...

0 Aryan Mokhtari, et al. ∙

research

∙ 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...

0 Murat A. Erdogdu, et al. ∙

research

∙ 01/31/2018

Graphon games

The study of strategic behavior in large scale networks via standard gam...

0 Francesca Parise, et al. ∙

research

∙ 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...

0 Francesca Parise, et al. ∙

research

∙ 10/08/2012

A Fast Distributed Proximal-Gradient Method

We present a distributed proximal-gradient method for optimizing the ave...

0 Annie I. Chen, et al. ∙

Asuman Ozdaglar

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