activity
20172020
most citedInertial Proximal Alternating Linearized Minimization (iPALM) for Nonconvex and Nonsmooth Problems

217 citations · 221 across the 4 of their papers we have counts for

collaborators

8 papers

cs.NI2020

Alternating Minimization Based First-Order Method for the Wireless Sensor Network Localization Problem

Eyal Gur, Shoham Sabach, Shimrit Shtern

We propose an algorithm for the Wireless Sensor Network localization problem, which is based on the well-known algorithmic framework of Alternating Minimization. We start with a no…

math.OC2020

Non-Convex Split Feasibility Problems: Models, Algorithms and Theory

Aviv Gibali, Shoham Sabach, Sergey Voldman

In this paper, we propose a catalog of iterative methods for solving the Split Feasibility Problem in the non-convex setting. We study four different optimization formulations of t…

math.OC2018

Optimization on Spheres: Models and Proximal Algorithms with Computational Performance Comparisons

D. Russell Luke, Shoham Sabach, Marc Teboulle

We present a unified treatment of the abstract problem of finding the best approximation between a cone and spheres in the image of affine transformations. Prominent instances of t…

cs.LG2018

Improved Complexities of Conditional Gradient-Type Methods with Applications to Robust Matrix Recovery Problems

Dan Garber, Shoham Sabach, Atara Kaplan

Motivated by robust matrix recovery problems such as Robust Principal Component Analysis, we consider a general optimization problem of minimizing a smooth and strongly convex loss…

math.OC2018

Nonconvex Lagrangian-Based Optimization: Monitoring Schemes and Global Convergence

Jérôme Bolte, Shoham Sabach, Marc Teboulle

We introduce a novel approach addressing global analysis of a difficult class of nonconvex-nonsmooth optimization problems within the important framework of Lagrangian-based method…

math.OC20174 cited

First Order Methods beyond Convexity and Lipschitz Gradient Continuity with Applications to Quadratic Inverse Problems

Jérôme Bolte, Shoham Sabach, Marc Teboulle +1

We focus on nonconvex and nonsmooth minimization problems with a composite objective, where the differentiable part of the objective is freed from the usual and restrictive global…