16 citations · 77 across the 28 of their papers we have counts for
4 papers · 1 filter
Online and Streaming Algorithms for Constrained -Submodular Maximization
Fabian Spaeh, Alina Ene, Huy L. Nguyen
Constrained -submodular maximization is a general framework that captures many discrete optimization problems such as ad allocation, influence maximization, personalized recomme…
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…
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…
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…