NIPS Workshop on Machine Learning Open Source Software, Whistler 2008

NIPS Workshop on Machine Learning Open Source Software, Whistler 2008

17 Lectures · Dec 12, 2008

About

We believe that the wide-spread adoption of open source software policies will have a tremendous impact on the field of machine learning. The goal of this workshop is to further support the current developments in this area and give new impulses to it. Following the success of the inaugural NIPS-MLOSS workshop held at NIPS 2006, the Journal of Machine Learning Research (JMLR) has started a new track for machine learning open source software initiated by the workshop's organizers. Many prominent machine learning researchers have co-authored a position paper advocating the need for open source software in machine learning. Furthermore, the workshop's organizers have set up a community website mloss.org where people can register their software projects, rate existing projects and initiate discussions about projects and related topics. This website currently lists 132 such projects including many prominent projects in the area of machine learning.

The main goal of this workshop is to bring the main practitioners in the area of machine learning open source software together in order to initiate processes which will help to further improve the development of this area. In particular, we have to move beyond a mere collection of more or less unrelated software projects and provide a common foundation to stimulate cooperation and interoperability between different projects. An important step in this direction will be a common data exchange format such that different methods can exchange their results more easily.

More information about workshop - http://mloss.org/workshop/nips08/

Related categories

Uploaded videos:

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09:42

Introduction and overwiew of the Machine Learning Open Source Software workshop

Sören Sonnenburg

Dec 20, 2008

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4103 Views

Introduction
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46:44

Octave

John W. Eaton

Dec 20, 2008

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14652 Views

Lecture
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26:52

Torch

Ronan Collobert

Dec 20, 2008

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4765 Views

Lecture
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17:52

Shark

Tobias Glasmachers

Dec 20, 2008

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5936 Views

Lecture
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20:20

Kernlab

Alexandros Karatzoglou

Dec 20, 2008

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10711 Views

Lecture
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12:00

Machine Learning Py (mlpy)

Davide Albanese

Dec 20, 2008

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9711 Views

Lecture
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13:19

MDP – Modular toolkit for Data Processing

Tiziano Zito

Dec 20, 2008

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4789 Views

Lecture
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36:05

What is a good mloss project

Dec 20, 2008

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2911 Views

Debate
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47:08

Matplotlib

John D. Hunter

Dec 20, 2008

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35719 Views

Invited Talk
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21:11

Disco

Ville H. Tuulos

Dec 20, 2008

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4277 Views

Lecture
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15:02

Nieme

Francis Maes

Dec 20, 2008

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3293 Views

Lecture
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14:04

libDAI

Joris Mooij

Dec 20, 2008

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6386 Views

Lecture
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11:04

BCPy2000

Jeremy Hill

Dec 20, 2008

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8057 Views

Lecture
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10:00

Model Monitor

Troy William Raeder

Dec 20, 2008

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3045 Views

Lecture
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19:42

RL Glue and Codecs Glue

Brian Tanner

Dec 20, 2008

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6094 Views

Lecture
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19:59

Experiment Databases for Machine Learning / BenchMarking Via Weka

Peter Reutemann

Dec 20, 2008

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6262 Views

Lecture
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29:22

Reproducible research

Sören Sonnenburg,

Mikio Braun,

Cheng Soon Ong

Dec 20, 2008

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3052 Views

Debate