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DLOPT: Deep Learning Optimization Library

Authors :
Camero, Andrés
Toutouh, Jamal
Alba, Enrique
Publication Year :
2018

Abstract

Deep learning hyper-parameter optimization is a tough task. Finding an appropriate network configuration is a key to success, however most of the times this labor is roughly done. In this work we introduce a novel library to tackle this problem, the Deep Learning Optimization Library: DLOPT. We briefly describe its architecture and present a set of use examples. This is an open source project developed under the GNU GPL v3 license and it is freely available at https://github.com/acamero/dlopt<br />Comment: 4 pages

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.1807.03523
Document Type :
Working Paper