15 citations · 35 across the 7 of their papers we have counts for
15 papers
High Probability Convergence for Accelerated Stochastic Mirror Descent
Alina Ene, Huy L. Nguyen
In this work, we describe a generic approach to show convergence with high probability for stochastic convex optimization. In previous works, either the convergence is only in expe…
META-STORM: Generalized Fully-Adaptive Variance Reduced SGD for Unbounded Functions
Zijian Liu, Ta Duy Nguyen, Thien Hang Nguyen +2
We study the application of variance reduction (VR) techniques to general non-convex stochastic optimization problems. In this setting, the recent work STORM [Cutkosky-Orabona '19]…
Adaptive Accelerated (Extra-)Gradient Methods with Variance Reduction
Zijian Liu, Ta Duy Nguyen, Alina Ene +1
In this paper, we study the finite-sum convex optimization problem focusing on the general convex case. Recently, the study of variance reduced (VR) methods and their accelerated v…
Projection-Free Bandit Optimization with Privacy Guarantees
Alina Ene, Huy L. Nguyen, Adrian Vladu
We design differentially private algorithms for the bandit convex optimization problem in the projection-free setting. This setting is important whenever the decision set has a com…
Adaptive and Universal Algorithms for Variational Inequalities with Optimal Convergence
Alina Ene, Huy L. Nguyen
We develop new adaptive algorithms for variational inequalities with monotone operators, which capture many problems of interest, notably convex optimization and convex-concave sad…
Adaptive Gradient Methods for Constrained Convex Optimization and Variational Inequalities
Alina Ene, Huy L. Nguyen, Adrian Vladu
We provide new adaptive first-order methods for constrained convex optimization. Our main algorithms AdaACSA and AdaAGD+ are accelerated methods, which are universal in the sense t…