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» An Analytic Learning System for Specializing Heuristics
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IJCAI
1993
13 years 6 months ago
An Analytic Learning System for Specializing Heuristics
This paper describes how meta-level theories are used for analytic learning in M U L T I - T A C . M U L T I - T A C operationalizes generic heuristics for constraint-satisfaction...
Steven Minton
GECCO
2007
Springer
144views Optimization» more  GECCO 2007»
13 years 8 months ago
Mixing independent classifiers
In this study we deal with the mixing problem, which concerns combining the prediction of independently trained local models to form a global prediction. We deal with it from the ...
Jan Drugowitsch, Alwyn Barry
AAAI
1993
13 years 6 months ago
Finding Accurate Frontiers: A Knowledge-Intensive Approach to Relational Learning
learning (EBL) component. In this paper we provide a brief review of FOIL and FOCL, then discuss how operationalizing a domain theory can adversely affect the accuracy of a learned...
Michael J. Pazzani, Clifford Brunk
AUSAI
2005
Springer
13 years 6 months ago
A Comparison of Evolutionary Methods for the Discovery of Local Search Heuristics
Abstract. Methods of adaptive constraint satisfaction have recently become of interest to overcome the limitations imposed on “black-box” search algorithms by the no free lunch...
Stuart Bain, John Thornton, Abdul Sattar
IEEEPACT
2008
IEEE
13 years 11 months ago
Feature selection and policy optimization for distributed instruction placement using reinforcement learning
Communication overheads are one of the fundamental challenges in a multiprocessor system. As the number of processors on a chip increases, communication overheads and the distribu...
Katherine E. Coons, Behnam Robatmili, Matthew E. T...