CONALD, June 11-13 Conference on Automated Learning and Discovery
General Information Submission Instructions Registration Workshops Travel and Accommodation Committees
Plenary Speakers

Tom Dietterich

Stuart Geman

David Heckerman

Michael Jordan

Daryl Pregibon

Herb Simon

Robert Tibshirani
Learning Causal Bayesian Networks

This workshop will focus on several topics in an area of automated learning and discovery that has flourished in the last several years: causal discovery. Interested participants are encouraged to submit papers on work in progress, some of which will be chosen for discussion during the workshop.

Depending on interest, we will select a subset of the topics below to cover in the workshop. For each topic, a few working papers among those submitted will be distributed beforehand, and a discussion leader will be assigned to lead an hour long discussion on the topic.

Topics

  • Identifying Causal Parameters
  • Handling Latent Variables
  • Computational Methods, i.e., issues of computational efficiency,
  • Model Scoring & Model Selection
  • Modeling Feedback
  • Case Studies

Organizers:

More Information

Contact conald@cs.cmu.edu for more information

The conference is sponsored by CMU's newly created Center for Automated Learning and Discovery.