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MLOSS 2013 : NIPS 2013 Workshop on Machine Learning Open Source Software: Towards Open Workflows


When Dec 9, 2013 - Dec 10, 2013
Where Lake Tahoe, NV, US
Submission Deadline Oct 9, 2013
Notification Due Oct 23, 2013
Categories    machine learning   computer science   open source

Call For Papers


Call for Contributions

Workshop on Machine Learning Open Source Software 2013:
Towards Open Workflows

at NIPS 2013, Lake Tahoe, Nevada, United States,
9th or 10th December, 2013


The NIPS Workshop on Machine Learning Open Source Software (MLOSS)
will held in Lake Tahoe (NV) on the 9th or 10th of December, 2013. 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 plan to have a workshop that is a mix of invited speakers,
contributed talks and discussion sessions. 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.

Important Dates

* Submission Date: October 9th, 2013
* Notification of Acceptance: October 23rd, 2013
* Workshop date: December 9th or 10th, 2013

Call for Contributions

The organizing committee is currently seeking abstracts for talks at
MLOSS 2013. MLOSS is a great opportunity for you to tell the community
about your use, development, philosophy, or other activities related
to open source software in machine learning. The committee will select
several submitted abstracts for 20-minute talks.

Submission Types

1. Software packages

This includes (but is not limited to) numeric packages (as e.g. R,
Octave, Python), machine learning toolboxes and implementations of
ML-algorithms, similar to the MLOSS track at JMLR
( ).

Submission format: 1 page abstract which must contain a link to the
project description on Any bells and whistles can be put on
your own project page, and of course provide this link on

Note: Projects must adhere to a recognized Open Source License
(cf. ) and the source code must
have been released at the time of submission. Submissions will be
reviewed based on the status of the project at the time of the
submission deadline. If accepted, the presentation must include a
software demo.

2. Other submissions

This category is open for position papers, interesting projects and
ideas that may not be new software themselves, but link to machine
learning and open source software.

Submission format: abstract with no page limit. Please note that there
will be no proceedings, i.e. the abstracts will not be published.

We look forward for submissions that are novel, exciting and that
appeal to the wider community. For more details see:

Please submit your contributions at


* Antti Honkela
University of Helsinki, Helsinki Institute for Information
Technology HIIT, Helsinki, Finland

* Cheng Soon Ong
NICTA, Victoria Research Laboratory, Melbourne, Australia

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