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» Iterated importance sampling in missing data problems
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EWCBR
2004
Springer
14 years 24 days ago
Facilitating CBR for Incompletely-Described Cases: Distance Metrics for Partial Problem Descriptions
A fundamental problem for case-based reasoning systems is how to select relevant prior cases. Numerous strategies have been developed for determining the similarity of prior cases,...
Steven Bogaerts, David B. Leake
BMCBI
2005
121views more  BMCBI 2005»
13 years 7 months ago
Evaluation of gene importance in microarray data based upon probability of selection
Background: Microarray devices permit a genome-scale evaluation of gene function. This technology has catalyzed biomedical research and development in recent years. As many import...
Li M. Fu, Casey S. Fu-Liu
MCS
2007
Springer
14 years 1 months ago
Random Feature Subset Selection for Ensemble Based Classification of Data with Missing Features
Abstract. We report on our recent progress in developing an ensemble of classifiers based algorithm for addressing the missing feature problem. Inspired in part by the random subsp...
Joseph DePasquale, Robi Polikar
AI
2010
Springer
13 years 7 months ago
Elicitation strategies for soft constraint problems with missing preferences: Properties, algorithms and experimental studies
We consider soft constraint problems where some of the preferences may be unspecified. This models, for example, settings where agents are distributed and have privacy issues, or ...
Mirco Gelain, Maria Silvia Pini, Francesca Rossi, ...
WSCG
2004
142views more  WSCG 2004»
13 years 8 months ago
Metropolis Iteration for Global Illumination
This paper presents a stochastic iteration algorithm solving the global illumination problem, where the random sampling is governed by classical importance sampling and also by th...
László Szirmay-Kalos, Bálazs ...