AMS-IMS-SIAM conference on machine learning and statistics

[John Lafferty]

An AMS-IMS-SIAM Joint Summer Research Conference will be held on the
topic of "Machine Learning, Statistics, and Discovery," with partial
funding from the NSF.  A preliminary announcement follows.  
Further information will be available from 
http://www.ams.org/meetings/src-shen.html


        Machine Learning, Statistics and Discovery

Machine learning is an active and rapidly growing area of research
that offers systematic and machine-implementable approaches to
extracting information from vast and complex data sources. The goal of
this conference is to assemble researchers from the disciplines of
computer science and statistics around the topical themes of support
vector machines and other large margin classifiers, boosting and
ensemble methods, new extensions of classification and regression,
methods for approximate inference, and application areas. A lively
exchange between the two communities is anticipated, which hopefully
will lead to cross-fertilization and new collaborations across
traditional academic disciplines. Young researchers, graduate
students, and underrepresented groups are encouraged to attend, as
they will be important for forming lasting "bridges" across the two
cultures in the future.

The site for the 2003 conference series is Snowbird Summer Resort,
located in the mountains of Snowbird, Utah. Check in is Saturday, June
21, and departure is Friday, June 27.

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Accepted principal speakers:

 Peter Bartlett     
 Leo Breiman  
 Tom Dietterich     
 David Heckerman    
 Ralf Herbrich      
 Tommi Jaakkola     
 Michael Kearns     
 Yi Lin             
 Steve Marron      
 Marina Meila       
 Art Owen           
 Tomaso Poggio      
 Robert Schapire    
 John Shawe-Taylor  
 Grace Wahba        
 Wing Wong          

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Tentative themes:

 Session 1: Overview of Machine Learning
 Session 2: Kernel Methods
 Session 3: Support Vector Machines
 Session 4: Boosting
 Session 5: Other Ensemble Methods
 Session 6: Extensions beyond Classification and Regression
 Session 7: Methods for Approximate Inference
 Session 8: Applications to Microarrays
 Session 9: Other Applications

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Organizers:

Joseph Verducci  Department of Statistics, Ohio State University
Xiaotong Shen    Department of Statistics, Ohio State University
John Lafferty    Computer Science Department, Carnegie Mellon University