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Machine Learning Open Source Software: Towards Open Workflows
Antti Honkela · Cheng Soon Ong

Tue Dec 10 07:30 AM -- 06:30 PM (PST) @ Harvey's Emerald Bay 5
Event URL: http://mloss.org/workshop/nips13/ »

Machine learning open source software (MLOSS) is one of the cornerstones of open science and reproducible research. Along with open access and open data, it enables free reuse and extension of current developments in machine learning. The mloss.org site exists to support a community creating a comprehensive open source machine learning environment, mainly by promoting new software implementations. This workshop aims to enhance the environment by fostering collaboration with the goal of creating tools that work with one another. Far from requiring integration into a single package, we believe that this kind of interoperability can also be achieved in a collaborative manner, which is especially suited to open source software development practices.

The workshop is aimed at all machine learning researchers who wish to have their algorithms and implementations included as a part of the greater open source machine learning environment. Continuing the tradition of well received workshops on MLOSS at NIPS 2006, NIPS 2008 and ICML 2010, we will have a workshop that is a mix of invited speakers, contributed talks and demos as well as a discussion session. For 2013, we focus on workflows and pipelines. Many algorithms and tools have reached a level of maturity which allows them to be reused and integrated into larger systems.

Author Information

Antti Honkela (University of Helsinki)
Cheng Soon Ong (NICTA, Melbourne)

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