Machine Learning

Machine learning is broad research area focused on pattern recognition, with strong ties to artificial intelligence, data mining, statistical pattern recognition, and predictive analytics. In the Machine Learning group at CCLS we work on designing new machine learning algorithms motivated by problems in real-world data. We also apply these algorithms to a variety of problems in the fields of energy management, computational biology, and the physical sciences.

Drs. Dutta, Waltz, Schevon and Emerson win an NSF award to work on a Distributed Framework for Learning on EEG Data obtained from Epilepsy Patients

Submitted by Dan on Wed, 09/09/2009 - 2:38pm

Project Name: EEGMine: A Distributed Framework for Learning
on EEG Data obtained from Epilepsy Patients

PI/Co-Pis: Haimonti Dutta, David Waltz, Catherine A Schevon
and Ronald Emerson
NSF Project ID: IIS-0916186
Award: $440,000 for 2 years

Drs. Waltz and Vapnik win an NSF grant to study Learning Using Hidden Information

Submitted by CCLSadmin on Fri, 07/31/2009 - 4:24pm

Dr. David Waltz and Dr. Valdimir Vapnik has been awarded a grant by the National Science Foundation to perform research in the area of "An Advanced Learning Paradigm: Learning Using Hidden Information". This project will be focusing on developing algorithms in the SVM family that allow extra information to be used effectively during training, with the understanding that this extra information will not be available during actual operation.