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Nadav Hallak
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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
792020
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
632016
Optimization problems involving group sparsity terms
A Beck, N Hallak
Mathematical Programming 178, 39-67, 2019
392019
Proximal mapping for symmetric penalty and sparsity
A Beck, N Hallak
SIAM Journal on Optimization 28 (1), 496-527, 2018
322018
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
232020
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
222021
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
152022
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
92020
On the minimization over sparse symmetric sets
A Beck, N Hallak
Optimisation Online repository, 2014
72014
An adaptive Lagrangian-based scheme for nonconvex composite optimization
N Hallak, M Teboulle
Mathematics of operations research 48 (4), 2337-2352, 2023
52023
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
42020
A non-Euclidean gradient descent method with sketching for unconstrained matrix minimization
N Hallak, M Teboulle
Operations Research Letters 47 (5), 421-426, 2019
32019
The regularized feasible directions method for nonconvex optimization
A Beck, N Hallak
Operations Research Letters 50 (5), 517-523, 2022
22022
An Augmented Lagrangian Approach for Problems With Random Matrix Composite Structure
D Greenstein, N Hallak
arXiv e-prints, arXiv: 2305.01055, 2023
12023
A Path-Based Approach to Constrained Sparse Optimization
N Hallak
SIAM Journal on Optimization 34 (1), 790-816, 2024
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
2023
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Articles 1–16