DLOPT: Deep Learning Optimization Library
July 10, 2018 ยท Entered Twilight ยท ๐ arXiv.org
"Last commit was 5.0 years ago (โฅ5 year threshold)"
Evidence collected by the PWNC Scanner
Repo contents: .gitignore, CONTRIBUTING.md, LICENSE, README.md, data, dlopt, docs, etc, examples, publications, requirements.txt, setup.py
Authors
Andrรฉs Camero, Jamal Toutouh, Enrique Alba
arXiv ID
1807.03523
Category
cs.LG: Machine Learning
Cross-listed
cs.NE,
stat.ML
Citations
9
Venue
arXiv.org
Repository
https://github.com/acamero/dlopt
โญ 12
Last Checked
4 months ago
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
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Machine Learning
๐ฎ
๐ฎ
The Ethereal
๐ฎ
๐ฎ
The Ethereal
Continuous control with deep reinforcement learning
๐
๐
Old Age
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
๐
๐
Old Age
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
๐
๐
Old Age
SGDR: Stochastic Gradient Descent with Warm Restarts
๐ฎ
๐ฎ
The Ethereal