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Predictive Search Distributions Edwin V. Bonilla edwin.bonilla@ed.ac.uk
 

Summary: Predictive Search Distributions
Edwin V. Bonilla edwin.bonilla@ed.ac.uk
Christopher K. I. Williams ckiw@inf.ed.ac.uk
Felix V. Agakov felixa@inf.ed.ac.uk
John Cavazos jcavazos@inf.ed.ac.uk
John Thomson John.Thomson@ed.ac.uk
Michael F. P. O'Boyle mob@inf.ed.ac.uk
School of Informatics, University of Edinburgh, 5 Forrest Hill, Edinburgh EH1 2QL, UK
Abstract
Estimation of Distribution Algorithms
(EDAs) are a popular approach to learn
a probability distribution over the "good"
solutions to a combinatorial optimization
problem. Here we consider the case where
there is a collection of such optimization
problems with learned distributions, and
where each problem can be characterized
by some vector of features. Now we can
define a machine learning problem to predict
the distribution of good solutions q(s|x) for

  

Source: Agakov, Felix - Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh
Edinburgh, University of - Division of Informatics, Institute for Adaptive and Neural Computation
Williams, Chris - Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh

 

Collections: Computer Technologies and Information Sciences