15 citations · 15 across the 1 of their papers we have counts for
4 papers
Dual Averaging is Surprisingly Effective for Deep Learning Optimization
Samy Jelassi, Aaron Defazio
First-order stochastic optimization methods are currently the most widely used class of methods for training deep neural networks. However, the choice of the optimizer has become a…
Extragradient with player sampling for faster Nash equilibrium finding
Carles Domingo Enrich, Samy Jelassi, Carles Domingo-Enrich +3
Data-driven modeling increasingly requires to find a Nash equilibrium in multi-player games, e.g. when training GANs. In this paper, we analyse a new extra-gradient method for Nash…
Global convergence of neuron birth-death dynamics
Grant Rotskoff, Samy Jelassi, Joan Bruna +1
Neural networks with a large number of parameters admit a mean-field description, which has recently served as a theoretical explanation for the favorable training properties of "o…
Smoothed analysis of the low-rank approach for smooth semidefinite programs
Thomas Pumir, Samy Jelassi, Nicolas Boumal
We consider semidefinite programs (SDPs) of size n with equality constraints. In order to overcome scalability issues, Burer and Monteiro proposed a factorized approach based on op…