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
Machine Learning and Reinforcement Learning for Manufacturing

In recent years there has been a flurry of research on statistics and machine learning applied to decision making and control. Progress has been made in many academic areas such as Reinforcement Learning, Neural Networks, Diagnostic Bayesian Networks. Applications are emerging in the control of continuous processes, batch processes (such as wafer fabrication), probabilistic diagnosis, and industrial engineering tasks such as optimal control of transfer lines or production scheduling.

Two kinds of presentations will be particularly encouraged for this workshop:

  1. Case studies of learning, applied statistics, datamining or neural networks applied to manufacturing systems.
  2. Advances in algorithms or theory that permit learning approaches to scale up to bigger problems.

Ideal participants: A mix of researchers from industrial labs, academics who work on manufacturing problems, reinforcement learning researchers, and others in the fields of statistics and machine learning who want to learn more about potential machine learning applications in industry.

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.