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05/26/2023
Exact Generalization Guarantees for (Regularized) Wasserstein Distributionally Robust Models
Wasserstein distributionally robust estimators have emerged as powerful ...
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11/15/2022
On the rate of convergence of Bregman proximal methods in constrained variational inequalities
We examine the last-iterate convergence rate of Bregman proximal methods...
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06/08/2022
Push–Pull with Device Sampling
We consider decentralized optimization problems in which a number of age...
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12/17/2021
Federated Learning with Heterogeneous Data: A Superquantile Optimization Approach
We present a federated learning framework that is designed to robustly d...
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07/05/2021
The Last-Iterate Convergence Rate of Optimistic Mirror Descent in Stochastic Variational Inequalities
In this paper, we analyze the local convergence rate of optimistic mirro...
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05/27/2021
Optimization in Open Networks via Dual Averaging
In networks of autonomous agents (e.g., fleets of vehicles, scattered se...
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12/21/2020
Multi-Agent Online Optimization with Delays: Asynchronicity, Adaptivity, and Optimism
Online learning has been successfully applied to many problems in which ...
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10/02/2020
Nonsmoothness in Machine Learning: specific structure, proximal identification, and applications
Nonsmoothness is often a curse for optimization; but it is sometimes a b...
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09/30/2020
First-order Optimization for Superquantile-based Supervised Learning
Classical supervised learning via empirical risk (or negative log-likeli...
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09/25/2020
Randomized Progressive Hedging methods for Multi-stage Stochastic Programming
Progressive Hedging is a popular decomposition algorithm for solving mul...
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03/23/2020
Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize Scaling
Owing to their stability and convergence speed, extragradient methods ha...
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02/25/2020
Device Heterogeneity in Federated Learning: A Superquantile Approach
We propose a federated learning framework to handle heterogeneous client...
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08/22/2019
On the convergence of single-call stochastic extra-gradient methods
Variational inequalities have recently attracted considerable interest i...
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12/10/2018
Asynchronous Distributed Learning with Sparse Communications and Identification
In this paper, we present an asynchronous optimization algorithm for dis...
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06/25/2018
A Distributed Flexible Delay-tolerant Proximal Gradient Algorithm
We develop and analyze an asynchronous algorithm for distributed convex ...
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01/17/2018
On the Proximal Gradient Algorithm with Alternated Inertia
In this paper, we investigate the attractive properties of the proximal ...
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07/11/2017
