Horn: A System for Parallel Training and Regularizing of Large-Scale Neural Networks

Autor:	Yoon, Edward J.
Rok vydání:	2016
Předmět:	Computer Science - Distributed Parallel and Cluster Computing Computer Science - Learning Computer Science - Neural and Evolutionary Computing
Druh dokumentu:	Working Paper
Popis:	I introduce a new distributed system for effective training and regularizing of Large-Scale Neural Networks on distributed computing architectures. The experiments demonstrate the effectiveness of flexible model partitioning and parallelization strategies based on neuron-centric computation model, with an implementation of the collective and parallel dropout neural networks training. Experiments are performed on MNIST handwritten digits classification including results.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1608.00781 Zobrazit plný text záznamu View this record from Arxiv