36 citations · 176 across the 39 of their papers we have counts for
3 papers · 1 filter
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-…
A general class of surrogate functions for stable and efficient reinforcement learning
Sharan Vaswani, Olivier Bachem, Simone Totaro +6
Common policy gradient methods rely on the maximization of a sequence of surrogate functions. In recent years, many such surrogate functions have been proposed, most without strong…
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…