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Optimal intervention in traffic networks
We present an efficient algorithm to identify which edge should be impro...
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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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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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Fictitious play in zero-sum 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 zero-sum game between...
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Personalized Federated Learning: A Meta-Learning 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 Model-Agnostic Meta-Reinforcement Learning
We consider Model-Agnostic Meta-Learning (MAML) methods for Reinforcemen...
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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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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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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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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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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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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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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 Block-Coordinate Maximization Burer-Monteiro 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 Proximal-Gradient Method
We present a distributed proximal-gradient method for optimizing the ave...
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