15 citations · 18 across the 2 of their papers we have counts for
4 papers · 1 filter
A new framework for the computation of Hessians
Robert M. Gower, Margarida P. Mello
We investigate the computation of Hessian matrices via Automatic Differentiation, using a graph model and an algebraic model. The graph model reveals the inherent symmetries involv…
Optimal mini-batch and step sizes for SAGA
Nidham Gazagnadou, Robert M. Gower, Joseph Salmon
Recently it has been shown that the step sizes of a family of variance reduced gradient methods called the JacSketch methods depend on the expected smoothness constant. In particul…
Stochastic Quasi-Gradient Methods: Variance Reduction via Jacobian Sketching
Robert M. Gower, Peter Richtárik, Francis Bach
We develop a new family of variance reduced stochastic gradient descent methods for minimizing the average of a very large number of smooth functions. Our method --JacSketch-- is m…
Stochastic Block BFGS: Squeezing More Curvature out of Data
Robert M. Gower, Donald Goldfarb, Peter Richtárik
We propose a novel limited-memory stochastic block BFGS update for incorporating enriched curvature information in stochastic approximation methods. In our method, the estimate of…