1 citations · 1 across the 4 of their papers we have counts for
4 papers
Two-stage stochastic algorithm for solving large-scale (non)-convex separable optimization problems under affine constraints
Benjamin Dubois-Taine, Laurent Pfeiffer, Nadia Oudjane +2
We consider nonsmooth optimization problems under affine constraints, where the objective consists of the average of the component functions of a large number of agents, and we…
Fast Stochastic Composite Minimization and an Accelerated Frank-Wolfe Algorithm under Parallelization
Benjamin Dubois-Taine, Francis Bach, Quentin Berthet +1
We consider the problem of minimizing the sum of two convex functions. One of those functions has Lipschitz-continuous gradients, and can be accessed via stochastic oracles, wherea…
Towards Noise-adaptive, Problem-adaptive (Accelerated) Stochastic Gradient Descent
Sharan Vaswani, Benjamin Dubois-Taine, Reza Babanezhad
We aim to make stochastic gradient descent (SGD) adaptive to (i) the noise in the stochastic gradients and (ii) problem-dependent constants. When minimizing smooth, strongly-…
SVRG Meets AdaGrad: Painless Variance Reduction
Benjamin Dubois-Taine, Sharan Vaswani, Reza Babanezhad +2
Variance reduction (VR) methods for finite-sum minimization typically require the knowledge of problem-dependent constants that are often unknown and difficult to estimate. To addr…