Hi list,
Please bare with me: a workshop announcment that is relevant to what we
do:
Workshop on Machine Learning Open Source Software 2015: Open Ecosystems
The ICML Workshop on Machine Learning Open Source Software (MLOSS) will
held in Lille, France on the 10th of July, 2015.
Important Dates:
* Submission Date: 28 April 2015, 23:59 UTC
* Notification of Acceptance: 11 May 2015
* Workshop date: 10 July 2015
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,
ICML 2010 and NIPS 2013, we plan to have a workshop that is a mix of
invited speakers, contributed talks and discussion/activity sessions. For
2015, we focus on building open ecosystems. Our invited speakers will
illustrate the process for Python and Julia through presenting modern
high-level high-performance computation engines, and we encourage
submissions that showcase the benefits of multiple tools in the same
ecosystem. All software presentations are required to include a live
demonstration. The workshop will also include an active session
(“hackathon”) for planning and starting to develop infrastructure for
measuring software impact.
We have two confirmed invited speakers
* John Myles White (Facebook), lead developer of Julia statistics and
machine learning (confirmed): "Julia for machine learning: high-level
syntax with compiled-code speed".
* Matthew Rocklin (Continuum Analytics), developer of Python
computational tools, in particular Blaze (confirmed): “Blaze, a modern
numerical engine with out-of-core and out-of-order computations”.
Cheers,
Gaël
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