
Optimal intervention in traffic networks
We present an efficient algorithm to identify which edge should be impro...
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Generalization of ModelAgnostic MetaLearning Algorithms: Recurring and Unseen Tasks
In this paper, we study the generalization properties of ModelAgnostic ...
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Multiagent Bayesian Learning with Adaptive Strategies: Convergence and Stability
We study learning dynamics induced by strategic agents who repeatedly pl...
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Fictitious play in zerosum stochastic games
We present fictitious play dynamics for the general class of stochastic ...
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GANs May Have No Nash Equilibria
Generative adversarial networks (GANs) represent a zerosum game between...
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Personalized Federated Learning: A MetaLearning Approach
The goal of federated learning is to design algorithms in which several ...
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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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Provably Convergent Policy Gradient Methods for ModelAgnostic MetaReinforcement Learning
We consider ModelAgnostic MetaLearning (MAML) methods for Reinforcemen...
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Last Iterate is Slower than Averaged Iterate in Smooth ConvexConcave Saddle Point Problems
In this paper we study the smooth convexconcave saddle point problem. S...
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Optimal dynamic information provision in traffic routing
We consider a tworoad dynamic routing game where the state of one of th...
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A Decentralized Proximal Pointtype Method for Saddle Point Problems
In this paper, we focus on solving a class of constrained nonconvex non...
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On the Convergence Theory of GradientBased ModelAgnostic MetaLearning Algorithms
In this paper, we study the convergence theory of a class of gradientba...
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Proximal Point Approximations Achieving a Convergence Rate of O(1/k) for Smooth ConvexConcave Saddle Point Problems: Optimistic Gradient and Extragradient Methods
In this paper we analyze the iteration complexity of the optimistic grad...
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A Unified Analysis of Extragradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point Approach
We consider solving convexconcave saddle point problems. We focus on tw...
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A Universally Optimal Multistage Accelerated Stochastic Gradient Method
We study the problem of minimizing a strongly convex and smooth function...
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Escaping Saddle Points in Constrained Optimization
In this paper, we focus on escaping from saddle points in smooth nonconv...
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Convergence Rate of BlockCoordinate Maximization BurerMonteiro Method for Solving Large SDPs
Semidefinite programming (SDP) with equality constraints arise in many o...
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Graphon games
The study of strategic behavior in large scale networks via standard gam...
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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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A Fast Distributed ProximalGradient Method
We present a distributed proximalgradient method for optimizing the ave...
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Asuman Ozdaglar
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