28 citations · 131 across the 41 of their papers we have counts for
4 papers · 1 filter
Efficient Optimization Algorithms for Robust Principal Component Analysis and Its Variants
Shiqian Ma, Necdet Serhat Aybat
Robust PCA has drawn significant attention in the last decade due to its success in numerous application domains, ranging from bio-informatics, statistics, and machine learning to…
Randomized Primal-Dual Methods with Adaptive Step Sizes
E. Yazdandoost Hamedani, A. Jalilzadeh, N. S. Aybat
In this paper we propose a class of randomized primal-dual methods to contend with large-scale saddle point problems defined by a convex-concave function $\mathcal{L}(\mathbf{x},y)…
Robust Accelerated Gradient Methods for Smooth Strongly Convex Functions
Necdet Serhat Aybat, Alireza Fallah, Mert Gurbuzbalaban +1
We study the trade-offs between convergence rate and robustness to gradient errors in designing a first-order algorithm. We focus on gradient descent (GD) and accelerated gradient…
A Primal-Dual Algorithm with Line Search for General Convex-Concave Saddle Point Problems
Erfan Yazdandoost Hamedani, Necdet Serhat Aybat
In this paper, we propose a primal-dual algorithm with a novel momentum term using the partial gradients of the coupling function that can be viewed as a generalization of the meth…