A group-theoretic framework for data augmentation

S Chen, E Dobriban, JH Lee - Journal of Machine Learning Research, 2020 - jmlr.org
Data augmentation is a widely used trick when training deep neural networks: in addition to
the original data, properly transformed data are also added to the training set. However, to …

Stochastic replica voting machine prediction of stable cubic and double perovskite materials and binary alloys

T Mazaheri, B Sun, J Scher-Zagier, AS Thind… - Physical Review …, 2019 - APS
A machine-learning approach that we term the “stochastic replica voting machine”(SRVM)
algorithm is presented and applied to a binary and a three-class classification problem in …

An online stochastic kernel machine for robust signal classification

RG Raj - 2019 53rd Asilomar Conference on Signals, Systems …, 2019 - ieeexplore.ieee.org
We present a novel variation of online kernel machines in which we exploit a consensus
based optimization mechanism to guide the evolution of decision functions drawn from a …

Matched Products and Dynamical Models for Multiplex Networks

DR DeFord - 2018 - search.proquest.com
MATCHED PRODUCTS AND DYNAMICAL MODELS FOR MULTIPLEX NETWORKS A
Thesis Submitted to the Faculty in partial fulfillment of the req Page 1 MATCHED …