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MCS
2007
Springer
14 years 4 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
GLVLSI
2006
IEEE
193views VLSI» more  GLVLSI 2006»
14 years 4 months ago
Optimizing noise-immune nanoscale circuits using principles of Markov random fields
As CMOS devices and operating voltages are scaled down, noise and defective devices will impact the reliability of digital circuits. Probabilistic computing compatible with CMOS o...
Kundan Nepal, R. Iris Bahar, Joseph L. Mundy, Will...
EMMCVPR
2001
Springer
14 years 2 months ago
A Hierarchical Markov Random Field Model for Figure-Ground Segregation
To segregate overlapping objects into depth layers requires the integration of local occlusion cues distributed over the entire image into a global percept. We propose to model thi...
Stella X. Yu, Tai Sing Lee, Takeo Kanade
CSFW
2010
IEEE
14 years 2 months ago
Approximation and Randomization for Quantitative Information-Flow Analysis
—Quantitative information-flow analysis (QIF) is an emerging technique for establishing information-theoretic confidentiality properties. Automation of QIF is an important step...
Boris Köpf, Andrey Rybalchenko
MCS
2010
Springer
14 years 6 days ago
Choosing Parameters for Random Subspace Ensembles for fMRI Classification
Abstract. Functional magnetic resonance imaging (fMRI) is a noninvasive and powerful method for analysis of the operational mechanisms of the brain. fMRI classification poses a sev...
Ludmila I. Kuncheva, Catrin O. Plumpton