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06/30/2023
An Oblivious Stochastic Composite Optimization Algorithm for Eigenvalue Optimization Problems
In this work, we revisit the problem of solving large-scale semidefinite...
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03/06/2023
Accelerated Rates between Stochastic and Adversarial Online Convex Optimization
Stochastic and adversarial data are two widely studied settings in onlin...
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02/24/2023
Differentially Private Algorithms for the Stochastic Saddle Point Problem with Optimal Rates for the Strong Gap
We show that convex-concave Lipschitz stochastic saddle point problems (...
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11/03/2022
Optimal Algorithms for Stochastic Complementary Composite Minimization
Inspired by regularization techniques in statistics and machine learning...
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06/02/2022
Faster Rates of Convergence to Stationary Points in Differentially Private Optimization
We study the problem of approximating stationary points of Lipschitz and...
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05/06/2022
Differentially Private Generalized Linear Models Revisited
We study the problem of (ϵ,δ)-differentially private learning of linear ...
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03/17/2022
A Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusion Problems
We study stochastic monotone inclusion problems, which widely appear in ...
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02/15/2022
Between Stochastic and Adversarial Online Convex Optimization: Improved Regret Bounds via Smoothness
Stochastic and adversarial data are two widely studied settings in onlin...
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07/12/2021
Differentially Private Stochastic Optimization: New Results in Convex and Non-Convex Settings
We study differentially private stochastic optimization in convex and no...
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06/23/2021
Best-Case Lower Bounds in Online Learning
Much of the work in online learning focuses on the study of sublinear up...
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06/10/2021
An Optimal Algorithm for Strict Circular Seriation
We study the problem of circular seriation, where we are given a matrix ...
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04/07/2021
Optimal Algorithms for Differentially Private Stochastic Monotone Variational Inequalities and Saddle-Point Problems
In this work, we conduct the first systematic study of stochastic variat...
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03/29/2021
The Complexity of Nonconvex-Strongly-Concave Minimax Optimization
This paper studies the complexity for finding approximate stationary poi...
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03/01/2021
Non-Euclidean Differentially Private Stochastic Convex Optimization
Differentially private (DP) stochastic convex optimization (SCO) is a fu...
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01/26/2021
Complementary Composite Minimization, Small Gradients in General Norms, and Applications to Regression Problems
Composite minimization is a powerful framework in large-scale convex opt...
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06/12/2020
Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses
Uniform stability is a notion of algorithmic stability that bounds the w...
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11/05/2018