1 citations · 1 across the 2 of their papers we have counts for
10 papers
Restarted Accelerated Primal-Dual Algorithms with Adaptive Stepsizes for Nonlinear Conic Constrained Convex Optimization
Necdet Serhat Aybat, Jinxin Wang
We propose restarted accelerated primal-dual algorithms with (non-monotone) backtracking (rAPDB) for convex nonlinear conic programs, with quadratically constrained quadratic progr…
A Stochastic GDA Method With Backtracking For Solving Nonconvex Concave Minimax Problems
Necdet Serhat Aybat, Qiushui Xu, Xuan Zhang +1
We propose a stochastic GDA (gradient descent ascent) method with backtracking (SGDA-B) to solve nonconvex-concave (NCC) minimax problems of the form: $\min_{\mathbf{x}} \max_y \su…
An Accelerated Primal Dual Algorithm with Backtracking for Decentralized Constrained Optimization
Qiushui Xu, Necdet Serhat Aybat, Mert Gürbüzbalaban
We propose a distributed accelerated primal-dual method with backtracking (D-APDB) for cooperative multi-agent constrained consensus optimization problems over an undirected networ…
Adaptive Algorithms for Robust Phase Retrieval
Zhong Zheng, Necdet Serhat Aybat, Shiqian Ma +1
This paper considers the robust phase retrieval, which can be cast as a nonsmooth and nonconvex composite optimization problem. We propose two first-order algorithms with adaptive…
Accelerated Gradient Methods with Biased Gradient Estimates: Risk Sensitivity, High-Probability Guarantees, and Large Deviation Bounds
Mert Gürbüzbalaban, Yasa Syed, Necdet Serhat Aybat
We study trade-offs between convergence rate and robustness to gradient errors in the context of first-order methods. Our focus is on generalized momentum methods (GMMs)--a broad c…
A Retraction-free Method for Nonsmooth Minimax Optimization over a Compact Manifold
Necdet Serhat Aybat, Jiang Hu, Zhanwang Deng
We study the minimax problem , where is a compact submanifold, is continuously differentiable in , is a closed, weak…