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» On Applying Classification to Schema Integration
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ICPR
2004
IEEE
14 years 11 months ago
Large Scale Feature Selection Using Modified Random Mutation Hill Climbing
Feature selection is a critical component of many pattern recognition applications. There are two distinct mechanisms for feature selection, namely the wrapper method and the filt...
Anil K. Jain, Michael E. Farmer, Shweta Bapna
KDD
2001
ACM
216views Data Mining» more  KDD 2001»
14 years 10 months ago
The distributed boosting algorithm
In this paper, we propose a general framework for distributed boosting intended for efficient integrating specialized classifiers learned over very large and distributed homogeneo...
Aleksandar Lazarevic, Zoran Obradovic
MICCAI
2010
Springer
13 years 8 months ago
Generalized Sparse Classifiers for Decoding Cognitive States in fMRI
The high dimensionality of functional magnetic resonance imaging (fMRI) data presents major challenges to fMRI pattern classification. Directly applying standard classifiers often ...
Bernard Ng, Arash Vahdat, Ghassan Hamarneh, Rafeef...
CVPR
2011
IEEE
13 years 1 months ago
Generalized Group Sparse Classifiers with Application in fMRI Brain Decoding
The perplexing effects of noise and high feature dimensionality greatly complicate functional magnetic resonance imaging (fMRI) classification. In this paper, we present a novel f...
Bernard Ng, Rafeef Abugharbieh
BMCBI
2006
202views more  BMCBI 2006»
13 years 10 months ago
DWARF - a data warehouse system for analyzing protein families
Background: The emerging field of integrative bioinformatics provides the tools to organize and systematically analyze vast amounts of highly diverse biological data and thus allo...
Markus Fischer, Quan K. Thai, Melanie Grieb, J&uum...