| On the almost sure convergence of stochastic gradient descent in non-convex problems P Mertikopoulos, N Hallak, A Kavis, V Cevher Advances in Neural Information Processing Systems 33, 1117-1128, 2020 | 117 | 2020 |
| On the minimization over sparse symmetric sets: projections, optimality conditions, and algorithms A Beck, N Hallak Mathematics of Operations Research 41 (1), 196-223, 2016 | 69 | 2016 |
| Optimization problems involving group sparsity terms A Beck, N Hallak Mathematical Programming 178, 39-67, 2019 | 46 | 2019 |
| Proximal mapping for symmetric penalty and sparsity A Beck, N Hallak SIAM Journal on Optimization 28 (1), 496-527, 2018 | 35 | 2018 |
| Regret minimization in stochastic non-convex learning via a proximal-gradient approach N Hallak, P Mertikopoulos, V Cevher International Conference on Machine Learning, 4008-4017, 2021 | 28 | 2021 |
| A dynamic alternating direction of multipliers for nonconvex minimization with nonlinear functional equality constraints E Cohen, N Hallak, M Teboulle Journal of Optimization Theory and Applications, 1-30, 2022 | 24 | 2022 |
| On the convergence to stationary points of deterministic and randomized feasible descent directions methods A Beck, N Hallak SIAM Journal on Optimization 30 (1), 56-79, 2020 | 24 | 2020 |
| Finding second-order stationary points in constrained minimization: A feasible direction approach N Hallak, M Teboulle Journal of Optimization Theory and Applications 186, 480-503, 2020 | 12 | 2020 |
| An adaptive Lagrangian-based scheme for nonconvex composite optimization N Hallak, M Teboulle Mathematics of Operations Research 48 (4), 2337-2352, 2023 | 10 | 2023 |
| On the minimization over sparse symmetric sets A Beck, N Hallak Optimisation Online repository, 2014 | 7 | 2014 |
| Efficient Proximal Mapping of the 1-path-norm of Shallow Networks F Latorre, P Rolland, N Hallak, V Cevher International Conference on Machine Learning, 5651-5661, 2020 | 4 | 2020 |
| A non-Euclidean gradient descent method with sketching for unconstrained matrix minimization N Hallak, M Teboulle Operations Research Letters 47 (5), 421-426, 2019 | 3 | 2019 |
| The regularized feasible directions method for nonconvex optimization A Beck, N Hallak Operations Research Letters 50 (5), 517-523, 2022 | 2 | 2022 |
| A path-based approach to constrained sparse optimization N Hallak SIAM Journal on Optimization 34 (1), 790-816, 2024 | 1 | 2024 |
| 1-Path-Norm Regularization of Deep Neural Networks F Latorre, A Bonnet, P Rolland, N Hallak, V Cevher LatinX in AI Workshop at ICML 2023 (Regular Deadline), 2023 | 1 | 2023 |
| An Augmented Lagrangian Approach for Problems With Random Matrix Composite Structure D Greenstein, N Hallak arXiv preprint arXiv:2305.01055, 2023 | 1 | 2023 |
| An Augmented Lagrangian Approach to Bi-Level Optimization via an Equilibrium Constrained Problem N Hallak, N Suissa | | 2025 |
| A study of first-order methods with a deterministic relative-error gradient Oracle N Hallak, KY Levy Forty-first International Conference on Machine Learning, 2024 | | 2024 |
Amir BeckProfessor, School of Mathematical Sciences, Tel-Aviv University, IsraelПідтверджена електронна адреса в tauex.tau.ac.il
