Nadav Hallak

Orcid: 0000-0002-0045-6636

According to our database1, Nadav Hallak authored at least 13 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
A Path-Based Approach to Constrained Sparse Optimization.
SIAM J. Optim., March, 2024

A Study of First-Order Methods with a Deterministic Relative-Error Gradient Oracle.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2022
The regularized feasible directions method for nonconvex optimization.
Oper. Res. Lett., 2022

A Dynamic Alternating Direction of Multipliers for Nonconvex Minimization with Nonlinear Functional Equality Constraints.
J. Optim. Theory Appl., 2022

2021
Regret Minimization in Stochastic Non-Convex Learning via a Proximal-Gradient Approach.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
On the Convergence to Stationary Points of Deterministic and Randomized Feasible Descent Directions Methods.
SIAM J. Optim., 2020

Finding Second-Order Stationary Points in Constrained Minimization: A Feasible Direction Approach.
J. Optim. Theory Appl., 2020

On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Efficient Proximal Mapping of the 1-path-norm of Shallow Networks.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
A non-Euclidean gradient descent method with sketching for unconstrained matrix minimization.
Oper. Res. Lett., 2019

Optimization problems involving group sparsity terms.
Math. Program., 2019

2018
Proximal Mapping for Symmetric Penalty and Sparsity.
SIAM J. Optim., 2018

2016
On the Minimization Over Sparse Symmetric Sets: Projections, Optimality Conditions, and Algorithms.
Math. Oper. Res., 2016


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