1 citations · 1 across the 2 of their papers we have counts for
3 papers
Anisotropic Gaussian Smoothing for Gradient-based Optimization
Andrew Starnes, Guannan Zhang, Viktor Reshniak +1
This article introduces a novel family of optimization algorithms - Anisotropic Gaussian Smoothing Gradient Descent (AGS-GD), AGS-Stochastic Gradient Descent (AGS-SGD), and AGS-Ada…
Hierarchical Bayesian approach for adaptive integration of Bragg peaks in time-of-flight neutron scattering data
Viktor Reshniak, Xiaoping Wang, Guannan Zhang +2
The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) operates in the event mode. Time-of-flight (TOF) information about each detected neutron is collected se…
Stable Anderson Acceleration for Deep Learning
Massimiliano Lupo Pasini, Junqi Yin, Viktor Reshniak +1
Anderson acceleration (AA) is an extrapolation technique designed to speed-up fixed-point iterations like those arising from the iterative training of DL models. Training DL models…