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20172026
most citedOn Adversarial Bias and the Robustness of Fair Machine Learning

37 citations · 56 across the 13 of their papers we have counts for

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5 papers · 1 filter

math.OC2025

Quasi-Self-Concordant Optimization with Lewis Weights

Alina Ene, Ta Duy Nguyen, Adrian Vladu

In this paper, we study the problem for a quasi-self-concordant function , where are $…

math.OC2023★ 1 cited

Improved Convergence in High Probability of Clipped Gradient Methods with Heavy Tails

Ta Duy Nguyen, Alina Ene, Huy L. Nguyen

In this work, we study the convergence \emph{in high probability} of clipped gradient methods when the noise distribution has heavy tails, ie., with bounded th moments, for some…

math.OC2023★ 4 cited

High Probability Convergence of Clipped-SGD Under Heavy-tailed Noise

Ta Duy Nguyen, Thien Hang Nguyen, Alina Ene +1

While the convergence behaviors of stochastic gradient methods are well understood \emph{in expectation}, there still exist many gaps in the understanding of their convergence with…

math.OC2023★ 2 cited

High Probability Convergence of Stochastic Gradient Methods

Zijian Liu, Ta Duy Nguyen, Thien Hang Nguyen +2

In this work, we describe a generic approach to show convergence with high probability for both stochastic convex and non-convex optimization with sub-Gaussian noise. In previous w…

math.OC2022

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…