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MLPACK: a scalable C++ machine learning library

Editors: Kevin Murphy, Bernhard Schölkopf Authors:

Alexander G. GrayAuthors Info & Claims

The Journal of Machine Learning Research, Volume 14, Issue 1

Pages 801 - 805

Published: 01 March 2013 Publication History

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Abstract

MLPACK is a state-of-the-art, scalable, multi-platform C++ machine learning library released in late 2011 offering both a simple, consistent API accessible to novice users and high performance and flexibility to expert users by leveraging modern features of C++. MLPACK provides cutting-edge algorithms whose benchmarks exhibit far better performance than other leading machine learning libraries. MLPACK version 1.0.3, licensed under the LGPL, is available at http://www.mlpack.org.

References

[1]

Davide Albanese, Roberto Visintainer, Stefano Merler, Samantha Riccadonna, Giuseppe Jurman, and Cesare Furlanello. mlpy: Machine Learning PYThon. 2012. Project homepage at http://mlpy.fbk.eu/.

Google Scholar

[2]

Samuel Burer and Renato D. C. Monteiro. A nonlinear programming algorithm for solving semidefinite programs via low-rank factorization. Mathematical Programming, 95(2):329-357, 2003.

Google Scholar

[3]

Chih-Chung Chang and Chih-Jen Lin. LIBSVM: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology, 2:27:1-27:27, 2011. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm.

Crossref

Google Scholar

[4]

Andrew J. Frank and Arthur Asuncion. UCI machine learning repository [http://archive.ics.uci.edu/ml], 2010. University of California, Irvine, School of Information and Computer Sciences.

Google Scholar

[5]

Mark Hall, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, and Ian H. Witten. The WEKA data mining software: An update. SIGKDD Explorations, 11(1), 2009.

Crossref

Google Scholar

[6]

Erik G. Learned-Miller and John W. Fisher. ICA using spacings estimates of entropy. Journal of Machine Learning Research, 4:1271-1295, December 2003. ISSN 1532-4435.

Crossref

Google Scholar

[7]

Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner. Gradient-based learning applied to document recognition. In Intelligent Signal Processing, pages 306-351. IEEE Press, 2001.

Google Scholar

[8]

William B. March, Parikshit Ram, and Alexander G. Gray. Fast Euclidean minimum spanning tree: algorithm, analysis, and applications. In Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '10, pages 603-612, 2010.

Crossref

Google Scholar

[9]

Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, VincentMichel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, Jake Vanderplas, Alexandre Passos, David Cournapeau, Matthieu Brucher, Matthieu Perrot, and Édouard Duchesnay. Scikit-learn: Machine learning in Python. Journal of Machine Learning Research, 12: 2825-2830, 2011.

Crossref

Google Scholar

[10]

Parikshit Ram and Alexander G. Gray. Density estimation trees. In Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '11, pages 627-635, New York, NY, USA, 2011. ACM.

Crossref

Google Scholar

[11]

Conrad Sanderson. Armadillo: An open source C++ linear algebra library for fast prototyping and computationally intensive experiments. Technical report, NICTA, 2010.

Google Scholar

[12]

Soeren Sonnenburg, Gunnar Raetsch, Sebastian Henschel, Christian Widmer, Jonas Behr, Alexander Zien, Fabio de Bona, Alexander Binder, Christian Gehl, and Vojtech Franc. The SHOGUN machine learning toolbox. Journal of Machine Learning Research, 11:1799-1802, June 2010.

Crossref

Google Scholar

[13]

Kai Yu, Tong Zhang, and Yihong Gong. Nonlinear learning using local coordinate coding. In Advances in Neural Information Processing Systems 22 (NIPS), pages 2223-2231, 2009.

Google Scholar

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Logan LGarcia JLofstead JSun XKougkas AWolf FShende SCulhane CAlam SJagode H(2022)LabStorProceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis10.5555/3571885.3571915(1-15)Online publication date: 13-Nov-2022
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Dushatskiy AAlderliesten TBosman P(2021)A Novel Approach to Designing Surrogate-assisted Genetic Algorithms by Combining Efficient Learning of Walsh Coefficients and DependenciesACM Transactions on Evolutionary Learning and Optimization10.1145/34531411:2(1-23)Online publication date: 29-Jul-2021
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Index Terms

MLPACK: a scalable C++ machine learning library
1. Computing methodologies
  1. Machine learning
2. Software and its engineering
  1. Software notations and tools
    1. General programming languages
      1. Language types
    2. Software libraries and repositories

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cover image The Journal of Machine Learning Research

The Journal of Machine Learning Research Volume 14, Issue 1

January 2013

3717 pages

ISSN:1532-4435

EISSN:1533-7928

Editors:
Kevin Murphy
Google
,
Bernhard Schölkopf
MPI for Intelligent Systems

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JMLR.org

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Published: 01 March 2013

Published in JMLR Volume 14, Issue 1

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Logan LGarcia JLofstead JSun XKougkas AWolf FShende SCulhane CAlam SJagode H(2022)LabStorProceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis10.5555/3571885.3571915(1-15)Online publication date: 13-Nov-2022
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Nguyen TMcCaskey A(2022)Extending Python for Quantum-classical Computing via Quantum Just-in-time CompilationACM Transactions on Quantum Computing10.1145/35444963:4(1-25)Online publication date: 27-Jul-2022
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Tapkee: an efficient dimension reduction library

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