On the minimization over sparse symmetric sets : projections, optimality conditions, and algorithms

von Beck, Amir
Veröffentlicht in Mathematics of operations research (2016)

The regularized feasible directions method for nonconvex optimization

von Beck, Amir
Veröffentlicht in Operations research letters (2022)

A non-Euclidean gradient descent method with sketching for unconstrained matrix minimization

von Hallak, Nadav
Veröffentlicht in Operations research letters (2019)

REGRET MINIMIZATION IN STOCHASTIC NON-CONVEX LEARNING VIA A PROXIMAL-GRADIENT APPROACH

von HALLAK, NADAV
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 6 of 16 (2022)

ON THE ALMOST SURE CONVERGENCE OF STOCHASTIC GRADIENT DESCENT IN NON-CONVEX PROBLEMS

von Mertikopoulos, Panayotis
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 2 of 27 (2021)