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Found 3 papers, 3 papers with code
Tensor train construction from tensor actions, with application to compression of large high order derivative tensors
We present a method for converting tensors into tensor train format based on actions of the tensor as a vector-valued multilinear function.
Numerical Analysis Numerical Analysis
Low Rank Saddle Free Newton: A Scalable Method for Stochastic Nonconvex Optimization
In this work we motivate the extension of Newton methods to the SA regime, and argue for the use of the scalable low rank saddle free Newton (LRSFN) method, which avoids forming the Hessian in favor of making a low rank approximation.
Inexact Newton Methods for Stochastic Non-Convex Optimization with Applications to Neural Network Training
We survey sub-sampled inexact Newton methods and consider their application in non-convex settings.
Optimization and Control Numerical Analysis
