ensmallen is a C++ header-only library for numerical optimization.
Documentation and downloads: http://ensmallen.org
ensmallen provides a simple set of abstractions for writing an objective function to optimize. It also provides a large set of standard and cutting-edge optimizers that can be used for virtually any numerical optimization task. These include full-batch gradient descent techniques, small-batch techniques, gradient-free optimizers, and constrained optimization.
Requirements
- C++ compiler with C++11 support
- Armadillo: http://arma.sourceforge.net
- OpenBLAS or Intel MKL or LAPACK (see Armadillo site for details)
Installation
ensmallen can be installed with CMake 3.3 or later. If CMake is not already available on your system, it can be obtained from https://cmake.org
If you are using an older system such as RHEL 7 or CentOS 7,
an updated version of CMake is also available via the EPEL repository via the cmake3 package.
License
Unless stated otherwise, the source code for ensmallen is licensed under the 3-clause BSD license (the "License"). A copy of the License is included in the "LICENSE.txt" file. You may also obtain a copy of the License at http://opensource.org/licenses/BSD-3-Clause .
Citation
Please cite the following paper if you use ensmallen in your research and/or software. Citations are useful for the continued development and maintenance of the library.
- S. Bhardwaj, R. Curtin, M. Edel, Y. Mentekidis, C. Sanderson. ensmallen: a flexible C++ library for efficient function optimization. Workshop on Systems for ML and Open Source Software at NIPS 2018.
@article{DBLP:journals/corr/abs-1810-09361,
author = {Shikhar Bhardwaj and
Ryan R. Curtin and
Marcus Edel and
Yannis Mentekidis and
Conrad Sanderson},
title = {ensmallen: a flexible {C++} library for efficient function optimization},
journal = {CoRR},
volume = {abs/1810.09361},
doi = {10.5281/zenodo.2008650},
year = {2018},
url = {http://arxiv.org/abs/1810.09361},
archivePrefix = {arXiv},
eprint = {1810.09361},
timestamp = {Wed, 31 Oct 2018 14:24:29 +0100},
biburl = {https://dblp.org/rec/bib/journals/corr/abs-1810-09361},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Developers and Contributors
- Ryan Curtin
- Dongryeol Lee
- Marcus Edel
- Sumedh Ghaisas
- Siddharth Agrawal
- Stephen Tu
- Shikhar Bhardwaj
- Vivek Pal
- Sourabh Varshney
- Chenzhe Diao
- Abhinav Moudgil
- Konstantin Sidorov
- Kirill Mishchenko
- Kartik Nighania
- Haritha Nair
- Moksh Jain
- Abhishek Laddha
- Arun Reddy
- Nishant Mehta
- Trironk Kiatkungwanglai
- Vasanth Kalingeri
- Zhihao Lou
- Conrad Sanderson
- Dan Timson
- N Rajiv Vaidyanathan
- Roberto Hueso
- Sayan Goswami