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 | 40 | 2016 |

Proximal mapping for symmetric penalty and sparsity A Beck, N Hallak SIAM Journal on Optimization 28 (1), 496-527, 2018 | 21 | 2018 |

Optimization problems involving group sparsity terms A Beck, N Hallak Mathematical Programming 178 (1), 39-67, 2019 | 11 | 2019 |

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 | 9 | 2020 |

On the minimization over sparse symmetric sets A Beck, N Hallak Optimisation Online repository, 2014 | 7 | 2014 |

On the almost sure convergence of stochastic gradient descent in non-convex problems P Mertikopoulos, N Hallak, A Kavis, V Cevher arXiv preprint arXiv:2006.11144, 2020 | 3 | 2020 |

Regret minimization in stochastic non-convex learning via a proximal-gradient approach N Hallak, P Mertikopoulos, V Cevher arXiv preprint arXiv:2010.06250, 2020 | 1 | 2020 |

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 | | 2020 |

Finding Second-Order Stationary Points in Constrained Minimization: A Feasible Direction Approach N Hallak, M Teboulle Journal of Optimization Theory and Applications 186 (2), 480-503, 2020 | | 2020 |

Efficient Proximal Mapping of the 1-path-norm of Shallow Networks FL Gómez, P Rolland, N Hallak, V Cevher | | 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 | | 2019 |