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IEEEPACT
2008
IEEE
14 years 2 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...
TEC
2002
133views more  TEC 2002»
13 years 7 months ago
Learning and optimization using the clonal selection principle
The clonal selection principle is used to explain the basic features of an adaptive immune response to an antigenic stimulus. It establishes the idea that only those cells that rec...
Leandro Nunes de Castro, Fernando J. Von Zuben
TMI
2002
155views more  TMI 2002»
13 years 7 months ago
Active Shape Model Segmentation with Optimal Features
Abstract--An active shape model segmentation scheme is presented that is steered by optimal local features, contrary to normalized first order derivative profiles, as in the origin...
Bram van Ginneken, Alejandro F. Frangi, Joes Staal...
NLPRS
2001
Springer
14 years 10 days ago
Named Entity Recognition using Machine Learning Methods and Pattern-Selection Rules
Named Entity recognition, as a task of providing important semantic information, is a critical first step in Information Extraction and QuestionAnswering system. This paper propos...
Choong-Nyoung Seon, Youngjoong Ko, Jeong-Seok Kim,...
GECCO
2006
Springer
130views Optimization» more  GECCO 2006»
13 years 11 months ago
Ensemble selection for evolutionary learning using information theory and price's theorem
This paper presents an information theoretic perspective on design and analysis of evolutionary algorithms. Indicators of solution quality are developed and applied not only to in...
Stuart W. Card, Chilukuri K. Mohan