A critical problem in clustering research is the definition of a proper metric to measure distances between points. Semi-supervised clustering uses the information provided by the ...
Information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. A common practice on this topic is so-called INFO-K-means, which perfor...
We propose a novel semi-supervised clustering method for the task of gene regulatory module discovery. The technique uses data on dna binding as prior knowledge to guide the proces...
Monitoring applications play an increasingly important role in many domains. They detect events in monitored systems and take actions such as invoke a program or notify an adminis...
Abstract—In classical image classification approaches, lowlevel features have been used. But the high dimensionality of feature spaces poses a challenge in terms of feature selec...
Rajeev Agrawal, Changhua Wu, William I. Grosky, Fa...