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math.OC2020★ 2 cited
Low Rank Saddle Free Newton: A Scalable Method for Stochastic Nonconvex Optimization
Thomas O'Leary-Roseberry, Nick Alger, Omar Ghattas
In modern deep learning, highly subsampled stochastic approximation (SA) methods are preferred to sample average approximation (SAA) methods because of large data sets as well as g…
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…