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  Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation

Townsend, J., Koep, N., & Weichwald, S. (2016). Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation. The Journal of Machine Learning Research, 17, 1-5. Retrieved from http://www.jmlr.org/papers/volume17/16-177/16-177.pdf.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-002D-1D77-1 Version Permalink: https://hdl.handle.net/11858/00-001M-0000-002D-48E4-1
Genre: Journal Article

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 Creators:
Townsend, J.1, Author
Koep, N.1, Author
Weichwald, Sebastian2, Author           
Affiliations:
1External Organizations, ou_persistent22              
2Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497647              

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Free keywords: Abt. Schölkopf
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Language(s): eng - English
 Dates: 2016
 Publication Status: Published online
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: TowKoeWei2016
URI: http://www.jmlr.org/papers/volume17/16-177/16-177.pdf
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Title: The Journal of Machine Learning Research
Source Genre: Journal
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Publ. Info: Cambridge, MA : MIT Press
Pages: - Volume / Issue: 17 Sequence Number: - Start / End Page: 1 - 5 Identifier: ISSN: 1532-4435
CoNE: https://pure.mpg.de/cone/journals/resource/111002212682020_1