activity
20132023
most citedScalable and efficient algorithms for the propagation of uncertainty from data through inference to prediction for large-scale problems, with application to flow of the Antarctic ice sheet

171 citations · 898 across the 46 of their papers we have counts for

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Showing 2019 · math.OCShow all

2 papers · 2 filters

math.OC2019★ 12 cited

Inexact Newton Methods for Stochastic Nonconvex Optimization with Applications to Neural Network Training

Thomas O'Leary-Roseberry, Nick Alger, Omar Ghattas

We study stochastic inexact Newton methods and consider their application in nonconvex settings. Building on the work of [R. Bollapragada, R. H. Byrd, and J. Nocedal, IMA Journal o…

math.OC2019★ 36 cited

Projected Stein Variational Newton: A Fast and Scalable Bayesian Inference Method in High Dimensions

Peng Chen, Keyi Wu, Joshua Chen +2

We propose a fast and scalable variational method for Bayesian inference in high-dimensional parameter space, which we call projected Stein variational Newton (pSVN) method. We exp…