Algorithm for Training Neural Networks on Resistive Device Arrays

Conjugate gradient algorithm for training neural networks

Training Deep Convolutional Neural Networks with Resistive Cross-Point Devices

In a previous work we have detailed the requirements for obtaining maximal deep learning performance benefit by implementing fully connected deep neural networks (DNN) in the form of arrays of resistive devices. Here we extend the concept of Resistive Processing Unit (RPU) devices to convolutional neural networks (CNNs). We show how to map the convolutional layers to fully connected RPU arrays ...

on descent spectral cg algorithm for training recurrent neural networks

In this paper, we evaluate the performance of a new class of conjugate gradient methods for training recurrent neural networks which ensure the sufficient descent property. The presented methods preserve the advantages of classical conjugate gradient methods and simultaneously avoid the usually inefficient restarts. Simulation results are also presented using three different recurrent neural ne...

Poly-HEMA as a drug delivery device for in vitro neural networks on micro-electrode arrays.

Delivery of pharmacological agents in vitro can often be a difficult, time consuming and costly process. In this paper, we describe an economical method for in vitro delivery using a hydrogel of poly hydroxyethyl methacrylate (PHEMA) that can absorb up to 50% of its weight of any water-solubilized pharmacological agent. This agent will then passively diffuse into surrounding media upon applicat...

A new training algorithm for feedforward neural networks