NIPS Workshop on Machine Learning Open Source Software, Whistler 2008

NIPS Workshop on Machine Learning Open Source Software, Whistler 2008

17 Videos · 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/

Videos

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47:08

Matplotlib

John D. Hunter

Dec 20, 2008

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35768 views

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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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4118 views

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11:04

BCPy2000

Jeremy Hill

Dec 20, 2008

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8109 views

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36:05

What is a good mloss project

Dec 20, 2008

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2917 views

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46:44

Octave

John W. Eaton

Dec 20, 2008

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14688 views

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19:59

Experiment Databases for Machine Learning / BenchMarking Via Weka

Peter Reutemann

Dec 20, 2008

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6265 views

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14:04

libDAI

Joris Mooij

Dec 20, 2008

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6387 views

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17:52

Shark

Tobias Glasmachers

Dec 20, 2008

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5942 views

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19:42

RL Glue and Codecs Glue

Brian Tanner

Dec 20, 2008

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6098 views

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10:00

Model Monitor

Troy William Raeder

Dec 20, 2008

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3049 views

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12:00

Machine Learning Py (mlpy)

Davide Albanese

Dec 20, 2008

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9725 views

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21:11

Disco

Ville H. Tuulos

Dec 20, 2008

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4289 views

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29:22

Reproducible research

Cheng Soon Ong,

Sören Sonnenburg,

Mikio Braun

Dec 20, 2008

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3058 views

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15:02

Nieme

Francis Maes

Dec 20, 2008

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3298 views

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26:52

Torch

Ronan Collobert

Dec 20, 2008

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4775 views

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20:20

Kernlab

Alexandros Karatzoglou

Dec 20, 2008

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10719 views

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13:19

MDP – Modular toolkit for Data Processing

Tiziano Zito

Dec 20, 2008

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4796 views