Existence and Approximation of Fixed Points of Bregman Firmly Nonexpansive Mappings in Reflexive Banach Spaces. - Simeon Reich; Shoham Sabach (Fixed-Point Algorithms for Inverse Problems in Science and Engineering, 2011)

Iterative Methods for Solving Systems of Variational Inequalities in Reflexive Banach Spaces. - Gábor Kassay; Simeon Reich; Shoham Sabach (SIAM J. Optim., 2011)

Products of Finitely Many Resolvents of Maximal Monotone Mappings in Reflexive Banach Spaces. - Shoham Sabach (SIAM J. Optim., 2011)

A Generalized Univariate Newton Method Motivated by Proximal Regularization. - Regina Sandra Burachik; C. Yalçin Kaya; Shoham Sabach (J. Optim. Theory Appl., 2012)

An improved ellipsoid method for solving convex differentiable optimization problems. - Amir Beck; Shoham Sabach (Oper. Res. Lett., 2012)

A first order method for finding minimal norm-like solutions of convex optimization problems. - Amir Beck; Shoham Sabach (Math. Program., 2014)

Proximal alternating linearized minimization for nonconvex and nonsmooth problems. - Jérôme Bolte; Shoham Sabach; Marc Teboulle (Math. Program., 2014)

Weiszfeld's Method: Old and New Results. - Amir Beck; Shoham Sabach (J. Optim. Theory Appl., 2015)

A simple algorithm for a class of nonsmooth convex-concave saddle-point problems. - Yoel Drori; Shoham Sabach; Marc Teboulle (Oper. Res. Lett., 2015)

Proximal Heterogeneous Block Implicit-Explicit Method and Application to Blind Ptychographic Diffraction Imaging. - Robert Hesse; D. Russell Luke; Shoham Sabach; Matthew K. Tam (SIAM J. Imaging Sci., 2015)

The Cyclic Block Conditional Gradient Method for Convex Optimization Problems. - Amir Beck; Edouard Pauwels; Shoham Sabach (SIAM J. Optim., 2015)

Inertial Proximal Alternating Linearized Minimization (iPALM) for Nonconvex and Nonsmooth Problems. - Thomas Pock; Shoham Sabach (SIAM J. Imaging Sci., 2016)

An Alternating Semiproximal Method for Nonconvex Regularized Structured Total Least Squares Problems. - Amir Beck; Shoham Sabach; Marc Teboulle (SIAM J. Matrix Anal. Appl., 2016)

On Fienup Methods for Regularized Phase Retrieval. - Edouard Pauwels; Amir Beck; Yonina C. Eldar; Shoham Sabach (CoRR, 2017)

A simple globally convergent algorithm for the nonsmooth nonconvex single source localization problem. - D. Russell Luke; Shoham Sabach; Marc Teboulle; Kobi Zatlawey (J. Glob. Optim., 2017)

A First Order Method for Solving Convex Bilevel Optimization Problems. - Shoham Sabach; Shimrit Shtern (SIAM J. Optim., 2017)

Fast Generalized Conditional Gradient Method with Applications to Matrix Recovery Problems. - Dan Garber; Shoham Sabach; Atara Kaplan (CoRR, 2018)

Nonconvex Lagrangian-Based Optimization: Monitoring Schemes and Global Convergence. - Jérôme Bolte; Shoham Sabach; Marc Teboulle (Math. Oper. Res., 2018)

Primal and dual predicted decrease approximation methods. - Amir Beck; Edouard Pauwels; Shoham Sabach (Math. Program., 2018)

First Order Methods Beyond Convexity and Lipschitz Gradient Continuity with Applications to Quadratic Inverse Problems. - Jérôme Bolte; Shoham Sabach; Marc Teboulle; Yakov Vaisbourd (SIAM J. Optim., 2018)

On Fienup Methods for Sparse Phase Retrieval. - Edouard Pauwels; Amir Beck; Yonina C. Eldar; Shoham Sabach (IEEE Trans. Signal Process., 2018)

Convex-Concave Backtracking for Inertial Bregman Proximal Gradient Algorithms in Non-Convex Optimization. - Mahesh Chandra Mukkamala; Peter Ochs; Thomas Pock; Shoham Sabach (CoRR, 2019)

Optimization on Spheres: Models and Proximal Algorithms with Computational Performance Comparisons. - D. Russell Luke; Shoham Sabach; Marc Teboulle (SIAM J. Math. Data Sci., 2019)

Non-Convex Split Feasibility Problems: Models, Algorithms and Theory. - Aviv Gibali; Shoham Sabach; Sergey Voldman (Open J. Math. Optim., 2020)

Stochastic proximal linear method for structured non-convex problems. - Tamir Hazan; Shoham Sabach; Sergey Voldman (Optim. Methods Softw., 2020)

Convex-Concave Backtracking for Inertial Bregman Proximal Gradient Algorithms in Nonconvex Optimization. - Mahesh Chandra Mukkamala; Peter Ochs; Thomas Pock; Shoham Sabach (SIAM J. Math. Data Sci., 2020)

Alternating Minimization Based First-Order Method for the Wireless Sensor Network Localization Problem. - Eyal Gur; Shoham Sabach; Shimrit Shtern (IEEE Trans. Signal Process., 2020)

Improved complexities of conditional gradient-type methods with applications to robust matrix recovery problems. - Dan Garber; Atara Kaplan; Shoham Sabach (Math. Program., 2021)

From Cluster Ranking to Document Ranking. - Egor Markovskiy; Fiana Raiber; Shoham Sabach; Oren Kurland (SIGIR, 2022)

Faster Lagrangian-Based Methods in Convex Optimization. - Shoham Sabach; Marc Teboulle (SIAM J. Optim., 2022)

Faster Projection-Free Augmented Lagrangian Methods via Weak Proximal Oracle. - Dan Garber; Tsur Livney; Shoham Sabach (AISTATS, 2023)

Resetting the Optimizer in Deep RL: An Empirical Study. - Kavosh Asadi; Rasool Fakoor; Shoham Sabach (NeurIPS, 2023)

TD Convergence: An Optimization Perspective. - Kavosh Asadi; Shoham Sabach; Yao Liu 009; Omer Gottesman; Rasool Fakoor (NeurIPS, 2023)

Convex Bi-Level Optimization Problems with Non-smooth Outer Objective Function. - Roey Merchav; Shoham Sabach (CoRR, 2023)

Convergent Nested Alternating Minimization Algorithms for Nonconvex Optimization Problems. - Eyal Gur; Shoham Sabach; Shimrit Shtern (Math. Oper. Res., 2023)

Direct, fast and convergent solvers for the non-convex and non-smooth TDoA localization problem. - Eyal Gur; Alon Amar; Shoham Sabach (Digit. Signal Process., 2023)

Nested Alternating Minimization with FISTA for Non-convex and Non-smooth Optimization Problems. - Eyal Gur; Shoham Sabach; Shimrit Shtern (J. Optim. Theory Appl., 2023)

Convex Bi-level Optimization Problems with Nonsmooth Outer Objective Function. - Roey Merchav; Shoham Sabach (SIAM J. Optim., 2023)

Krylov Cubic Regularized Newton: A Subspace Second-Order Method with Dimension-Free Convergence Rate. - Ruichen Jiang; Parameswaran Raman; Shoham Sabach; Aryan Mokhtari; Mingyi Hong 001; Volkan Cevher (AISTATS, 2024)

TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models. - Zuxin Liu; Jesse Zhang; Kavosh Asadi; Yao Liu 009; Ding Zhao; Shoham Sabach; Rasool Fakoor (ICLR, 2024)

Learning the Target Network in Function Space. - Kavosh Asadi; Yao Liu 009; Shoham Sabach; Ming Yin; Rasool Fakoor (ICML, 2024)

MADA: Meta-Adaptive Optimizers Through Hyper-Gradient Descent. - Kaan Ozkara; Can Karakus; Parameswaran Raman; Mingyi Hong 001; Shoham Sabach; Branislav Kveton; Volkan Cevher (ICML, 2024)

Comparing Few to Rank Many: Active Human Preference Learning using Randomized Frank-Wolfe. - Kiran Koshy Thekumparampil; Gaurush Hiranandani; Kousha Kalantari; Shoham Sabach; Branislav Kveton (CoRR, 2024)

A semi-Bregman proximal alternating method for a class of nonconvex problems: local and global convergence analysis. - Eyal Cohen; D. Russell Luke; Titus Pinta; Shoham Sabach; Marc Teboulle (J. Glob. Optim., 2024)

A Globally Convergent Inertial First-Order Optimization Method for Multidimensional Scaling. - Noga Ram; Shoham Sabach (J. Optim. Theory Appl., 2024)

MoXCo: How I learned to stop exploring and love my local minima? - Esha Singh; Shoham Sabach; Yu-Xiang Wang 003 (CPAL, 2025)

A dual-based first-order algorithm for ToA asynchronous localization and synchronization. - Eyal Gur; Alon Amar; Shoham Sabach (Signal Process., 2025)

A Proximal Operator for Inducing 2:4-Sparsity. - Jonas M. Kübler; Yu-Xiang Wang 003; Shoham Sabach; Navid Ansari; Matthäus Kleindessner; Kailash Budhathoki; Volkan Cevher; George Karypis (Trans. Mach. Learn. Res., 2025)

νSAM: Memory-Efficient Sharpness-Aware Minimization via Nuclear Norm Constraints. - Thomas Pethick; Parameswaran Raman; Lenon Minorics; Mingyi Hong 001; Shoham Sabach; Volkan Cevher (Trans. Mach. Learn. Res., 2025)

ProxSparse: Regularized Learning of Semi-Structured Sparsity Masks for Pretrained LLMs. - Hongyi Liu; Rajarshi Saha; Zhen Jia; Youngsuk Park; Jiaji Huang; Shoham Sabach; Yu-Xiang Wang 003; George Karypis (CoRR, 2025)

C-3DPO: Constrained Controlled Classification for Direct Preference Optimization. - Kavosh Asadi; Julien Han; Xingzi Xu; Dominique Perrault-Joncas; Shoham Sabach; Karim Bouyarmane; Mohammad Ghavamzadeh (CoRR, 2025)

FisherSFT: Data-Efficient Supervised Fine-Tuning of Language Models Using Information Gain. - Rohan Deb; Kiran Koshy Thekumparampil; Kousha Kalantari; Gaurush Hiranandani; Shoham Sabach; Branislav Kveton (CoRR, 2025)