PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Development Projects for the Causality Workbench
Isabelle Guyon, Jean-Philippe Pellet and Alexander Statnikov
In: AAAI Spring symposium on AI for development, 23-24 Mar 2010, Stanford, California, USA.


The Causality Workbench project provides an environment to test causal discovery algorithms. Via a web portal, we provide a number of resources, including a repository of datasets, models, and software packages, and a virtual laboratory allowing users to benchmark causal discovery algorithms by performing virtual experiments to study artificial causal systems. We regularly organize competitions. In this paper, we explore the opportunities offered by development applications.

PDF - Requires Adobe Acrobat Reader or other PDF viewer.
EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:5772
Deposited By:Isabelle Guyon
Deposited On:08 March 2010