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...
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...
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...
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...
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...