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» An Analytic Learning System for Specializing Heuristics
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IJCAI
1993
14 years 11 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»
15 years 2 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
92
Voted
AAAI
1993
14 years 11 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
81
Voted
AUSAI
2005
Springer
15 years 6 days 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
103
Voted
IEEEPACT
2008
IEEE
15 years 4 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...