17 citations · 122 across the 12 of their papers we have counts for
12 papers
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…
Unified Analysis of Stochastic Gradient Methods for Composite Convex and Smooth Optimization
Ahmed Khaled, Othmane Sebbouh, Nicolas Loizou +2
We present a unified theorem for the convergence analysis of stochastic gradient algorithms for minimizing a smooth and convex loss plus a convex regularizer. We do this by extendi…
Sketched Newton-Raphson
Rui Yuan, Alessandro Lazaric, Robert M. Gower
We propose a new globally convergent stochastic second order method. Our starting point is the development of a new Sketched Newton-Raphson (SNR) method for solving large scale non…
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…
Greedy stochastic algorithms for entropy-regularized optimal transport problems
Brahim Khalil Abid, Robert M. Gower
Optimal transport (OT) distances are finding evermore applications in machine learning and computer vision, but their wide spread use in larger-scale problems is impeded by their h…