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Nadav Hallak
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2020 – today
- 2024
- [j9]Nadav Hallak
:
A Path-Based Approach to Constrained Sparse Optimization. SIAM J. Optim. 34(1): 790-816 (2024) - [c4]Nadav Hallak, Kfir Yehuda Levy:
A Study of First-Order Methods with a Deterministic Relative-Error Gradient Oracle. ICML 2024 - 2022
- [j8]Eyal Cohen, Nadav Hallak
A Dynamic Alternating Direction of Multipliers for Nonconvex Minimization with Nonlinear Functional Equality Constraints. J. Optim. Theory Appl. 193(1): 324-353 (2022) - [j7]Amir Beck
The regularized feasible directions method for nonconvex optimization. Oper. Res. Lett. 50(5): 517-523 (2022) - 2021
- [c3]Nadav Hallak, Panayotis Mertikopoulos, Volkan Cevher
Regret Minimization in Stochastic Non-Convex Learning via a Proximal-Gradient Approach. ICML 2021: 4008-4017 - 2020
- [j6]Nadav Hallak
Finding Second-Order Stationary Points in Constrained Minimization: A Feasible Direction Approach. J. Optim. Theory Appl. 186(2): 480-503 (2020) - [j5]Amir Beck, Nadav Hallak
On the Convergence to Stationary Points of Deterministic and Randomized Feasible Descent Directions Methods. SIAM J. Optim. 30(1): 56-79 (2020) - [c2]Fabian Latorre, Paul Rolland, Nadav Hallak, Volkan Cevher
Efficient Proximal Mapping of the 1-path-norm of Shallow Networks. ICML 2020: 5651-5661 - [c1]Panayotis Mertikopoulos, Nadav Hallak, Ali Kavis, Volkan Cevher
On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems. NeurIPS 2020 - [i3]Panayotis Mertikopoulos, Nadav Hallak, Ali Kavis, Volkan Cevher:
On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems. CoRR abs/2006.11144 (2020) - [i2]Fabian Latorre, Paul Rolland, Nadav Hallak, Volkan Cevher:
Efficient Proximal Mapping of the 1-path-norm of Shallow Networks. CoRR abs/2007.01003 (2020) - [i1]Nadav Hallak, Panayotis Mertikopoulos, Volkan Cevher:
Regret minimization in stochastic non-convex learning via a proximal-gradient approach. CoRR abs/2010.06250 (2020)
2010 – 2019
- 2019
- [j4]Amir Beck, Nadav Hallak
Optimization problems involving group sparsity terms. Math. Program. 178(1-2): 39-67 (2019) - [j3]Nadav Hallak
A non-Euclidean gradient descent method with sketching for unconstrained matrix minimization. Oper. Res. Lett. 47(5): 421-426 (2019) - 2018
- [j2]Amir Beck, Nadav Hallak
Proximal Mapping for Symmetric Penalty and Sparsity. SIAM J. Optim. 28(1): 496-527 (2018) - 2016
- [j1]Amir Beck, Nadav Hallak
On the Minimization Over Sparse Symmetric Sets: Projections, Optimality Conditions, and Algorithms. Math. Oper. Res. 41(1): 196-223 (2016)
Coauthor Index
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