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» Adaptive importance sampling in general mixture classes
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BMCBI
2006
173views more  BMCBI 2006»
13 years 7 months ago
Kernel-based distance metric learning for microarray data classification
Background: The most fundamental task using gene expression data in clinical oncology is to classify tissue samples according to their gene expression levels. Compared with tradit...
Huilin Xiong, Xue-wen Chen
TMI
2010
206views more  TMI 2010»
13 years 2 months ago
Random Subspace Ensembles for fMRI Classification
Classification of brain images obtained through functional magnetic resonance imaging (fMRI) poses a serious challenge to pattern recognition and machine learning due to the extrem...
Ludmila I. Kuncheva, Juan José Rodrí...
CORR
2011
Springer
186views Education» more  CORR 2011»
13 years 2 months ago
Similarity Join Size Estimation using Locality Sensitive Hashing
Similarity joins are important operations with a broad range of applications. In this paper, we study the problem of vector similarity join size estimation (VSJ). It is a generali...
Hongrae Lee, Raymond T. Ng, Kyuseok Shim
HPDC
2010
IEEE
13 years 8 months ago
Exploring application and infrastructure adaptation on hybrid grid-cloud infrastructure
Clouds are emerging as an important class of distributed computational resources and are quickly becoming an integral part of production computational infrastructures. An importan...
Hyunjoo Kim, Yaakoub El Khamra, Shantenu Jha, Mani...
GIS
2005
ACM
14 years 8 months ago
Adaptive nearest neighbor queries in travel time networks
Nearest neighbor (NN) searches represent an important class of queries in geographic information systems (GIS). Most nearest neighbor algorithms rely on static distance informatio...
Wei-Shinn Ku, Roger Zimmermann, Haojun Wang, Chi-N...