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147
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PR
2006
164views more  PR 2006»
15 years 3 months ago
Locally linear metric adaptation with application to semi-supervised clustering and image retrieval
Many computer vision and pattern recognition algorithms are very sensitive to the choice of an appropriate distance metric. Some recent research sought to address a variant of the...
Hong Chang, Dit-Yan Yeung
KDD
2007
ACM
276views Data Mining» more  KDD 2007»
16 years 4 months ago
Nonlinear adaptive distance metric learning for clustering
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Jianhui Chen, Zheng Zhao, Jieping Ye, Huan Liu
PDCAT
2004
Springer
15 years 9 months ago
Parallel Computing Platform for the Agent-Based Modeling of Multicellular Biological Systems
Abstract. Agent-based simulation of large multicellular biological systems has become a viable option owing to affordable parallel computers, such as Beowulf-style clusters. We de...
Toh Da-Jun, Francis Tang, Travis Lee, Deepak Sarda...
123
Voted
CLUSTER
2008
IEEE
15 years 10 months ago
Reliable adaptable Network RAM
Abstract—We present reliability solutions for adaptable Network RAM systems running on general-purpose clusters. Network RAM allows nodes with over-committed memory to swap pages...
Tia Newhall, Daniel Amato, Alexandr Pshenichkin
130
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PRIB
2009
Springer
135views Bioinformatics» more  PRIB 2009»
15 years 10 months ago
Sequential Hierarchical Pattern Clustering
Abstract. Clustering is a widely used unsupervised data analysis technique in machine learning. However, a common requirement amongst many existing clustering methods is that all p...
Bassam Farran, Amirthalingam Ramanan, Mahesan Nira...