#Number
TR-PDS-1995-005

#Title
A Parallel Algorithm for Optimal Margin Classifiers


#Author
Ross Baldick and Craig M. Chase


#Abstract
  In a recent paper, Boser et al. describe an algorithm based
  on quadratic programming for training a classifier that maximizes
  the classification margin between dichotomous classes of patterns.
  Boser et al.'s algorithm can treat classification problems
  having parameter spaces of very high dimension because it solves the
  problem in the dual space.  If the margin in the original problem is
  positive, that is, if there exists a hyperplane separating the two
  classes, then the dual problem is a convex quadratic program.  The
  dual problem has dimension equal to the number of patterns.

  Unfortunately, the number of patterns, while finite, is also very
  large.  Consequently, Boser et al.'s algorithm requires
  considerable computational effort to execute.  In this paper we
  propose a parallel implementation of Boser et al.'s algorithm.
  We demonstrate the implementation on an example database and analyze
  its performance.  We also indicate extensions to other problems
  of similar structure.  

	
#Bib
@TechReport{BC95,
  author =       "Ross Baldick and Craig. M. Chase",
  title =        "A Parallel Algorithm for Optimal Margin Classifiers",
  institution =  "Parallel and Distributed Systems Laboratory,
                  ECE Dept., University of Texas at Austin",
  year =         "1995",
  number =    "TR-PDS-1995-005",
  note =      "submitted to Symposium on Parallel and Distributed
                  Processing", 
  note =      "available via ftp or WWW at maple.ece.utexas.edu
		  as technical report TR-PDS-1995-005"
}