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

Fast Stochastic Algorithms for Low-rank and Nonsmooth Matrix Problems. - Dan Garber; Atara Kaplan (AISTATS, 2019)

Low-Rank Extragradient Method for Nonsmooth and Low-Rank Matrix Optimization Problems. - Atara Kaplan; Dan Garber (NeurIPS, 2021)

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

Low-Rank Mirror-Prox for Nonsmooth and Low-Rank Matrix Optimization Problems. - Dan Garber; Atara Kaplan (CoRR, 2022)

Efficiency of First-Order Methods for Low-Rank Tensor Recovery with the Tensor Nuclear Norm Under Strict Complementarity. - Dan Garber; Atara Kaplan (CoRR, 2023)

On the Efficient Implementation of the Matrix Exponentiated Gradient Algorithm for Low-Rank Matrix Optimization. - Dan Garber; Atara Kaplan (Math. Oper. Res., 2023)

Low-rank extragradient methods for scalable semidefinite optimization. - Dan Garber; Atara Kaplan (Oper. Res. Lett., 2025)