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PR
2006
164views more  PR 2006»
13 years 9 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»
14 years 9 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
14 years 2 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...
CLUSTER
2008
IEEE
14 years 3 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
PRIB
2009
Springer
135views Bioinformatics» more  PRIB 2009»
14 years 3 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...