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The need for open source software in machine learning

Sonnenburg, Soren; Braun, Mikio L; Ong, Cheng Soon; Bengio, Samy; Bottou, Leon; Holmes, Geoffrey; LeCun, Yann; Mueller, Klaus-Robert; Pereira, Fernando; Rasmussen, Carl E; Raetsch, Gunnar; Schoelkopf, Bernhard; Smola, Alexander; Vincent, Pascal; Weston, Jason; Williamson, Robert

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Open source tools have recently reached a level of maturity which makes them suitable for building large-scale real-world systems. At the same time, the field of machine learning has developed a large body of powerful learning algorithms for diverse applications. However, the true potential of these methods is not used, since existing implementations are not openly shared, resulting in software with low usability, and weak interoperability. We argue that this situation can be...[Show more]

dc.contributor.authorSonnenburg, Soren
dc.contributor.authorBraun, Mikio L
dc.contributor.authorOng, Cheng Soon
dc.contributor.authorBengio, Samy
dc.contributor.authorBottou, Leon
dc.contributor.authorHolmes, Geoffrey
dc.contributor.authorLeCun, Yann
dc.contributor.authorMueller, Klaus-Robert
dc.contributor.authorPereira, Fernando
dc.contributor.authorRasmussen, Carl E
dc.contributor.authorRaetsch, Gunnar
dc.contributor.authorSchoelkopf, Bernhard
dc.contributor.authorSmola, Alexander
dc.contributor.authorVincent, Pascal
dc.contributor.authorWeston, Jason
dc.contributor.authorWilliamson, Robert
dc.date.accessioned2009-05-22T01:55:10Z
dc.date.accessioned2010-12-20T06:05:49Z
dc.date.available2009-05-22T01:55:10Z
dc.date.available2010-12-20T06:05:49Z
dc.identifier.citationJournal of Machine Learning Research 8 (2007): 2443-2466
dc.identifier.issn1532-4435
dc.identifier.issn1533-7928
dc.identifier.urihttp://hdl.handle.net/10440/309
dc.identifier.urihttp://digitalcollections.anu.edu.au/handle/10440/309
dc.description.abstractOpen source tools have recently reached a level of maturity which makes them suitable for building large-scale real-world systems. At the same time, the field of machine learning has developed a large body of powerful learning algorithms for diverse applications. However, the true potential of these methods is not used, since existing implementations are not openly shared, resulting in software with low usability, and weak interoperability. We argue that this situation can be significantly improved by increasing incentives for researchers to publish their software under an open source model. Additionally, we outline the problems authors are faced with when trying to publish algorithmic implementations of machine learning methods. We believe that a resource of peer reviewed software accompanied by short articles would be highly valuable to both the machine learning and the general scientific community.
dc.format24 pages
dc.publisherMIT Press
dc.rightshttp://www.sherpa.ac.uk/romeo/search.php "Author can archive pre-print (ie pre-refereeing) ... [but] cannot archive post-print (ie final draft post-refereeing) … [and] subject to Restrictions, 3 months for STM, author can archive publisher's version/PDF ... on institutional repository; Publisher copyright and source must be acknowledged; Must link to journal homepage; Publishers’ copyright statement must be included; Publisher's version/PDF must be used for post-print deposit." - from SHERPA/RoMEO site (as at 18/02/10)
dc.sourceJournal of Machine Learning Research
dc.source.urihttp://jmlr.csail.mit.edu/papers/volume8/sonnenburg07a/sonnenburg07a.pdf
dc.subjectmachine learning
dc.subjectopen source
dc.subjectreproducibility
dc.subjectalgorithms
dc.subjectsoftware
dc.titleThe need for open source software in machine learning
dc.typeJournal article
local.description.notesAffiliation in article: Smola, Alexander and Williamson, Robert also with NICTA, ACT. Article written under names Gunnar Rätsch; Bernhard Schölkopf
local.identifier.citationvolume8
dc.date.issued2007-10
local.identifier.absfor080109
local.identifier.ariespublicationu8803936xPUB163
local.type.statusPublished Version
local.contributor.affiliationSonnenburg, Soren, Fraunhofer Institute, Germany
local.contributor.affiliationBraun, Mikio L, Technical University of Berlin
local.contributor.affiliationOng, Cheng Soon, Max Planck Society
local.contributor.affiliationBengio, Samy, Google
local.contributor.affiliationBottou, Leon, NEC Laboratories America Inc
local.contributor.affiliationHolmes, Geoffrey, University of Waikato
local.contributor.affiliationLeCun, Yann, New York University
local.contributor.affiliationMueller, Klaus-Robert, Technical University of Berlin
local.contributor.affiliationPereira, Fernando, University of Pennsylvania
local.contributor.affiliationRasmussen, Carl E, University of Cambridge
local.contributor.affiliationRaetsch, Gunnar, Max Planck Society
local.contributor.affiliationSchoelkopf, Bernhard, Max Planck Institute for Biological Cybernetics
local.contributor.affiliationSmola, Alexander, Research School of Information Sciences and Engineering, Computer Sciences Laboratory
local.contributor.affiliationVincent, Pascal, University of Montreal
local.contributor.affiliationWeston, Jason, NEC Laboratories America Inc
local.contributor.affiliationWilliamson, Robert, Research School of Information Sciences and Engineering, Computer Sciences Laboratory
local.bibliographicCitation.issueOct
local.bibliographicCitation.startpage2443
local.bibliographicCitation.lastpage2466
dc.date.updated2015-12-09T07:19:18Z
local.identifier.scopusID2-s2.0-35748939406
CollectionsANU Research Publications

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