Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...
Zhenyu Lu, Anand I. Rughani, Bruce I. Tranmer, Jos...
The past few decades have witnessed a chronic and widening imbalance among processor bandwidth, disk capacity, and access speed of disk. According to Amdhal's law, the perfor...
We present a new class of problems, called resource-bounded information gathering for correlation clustering. Our goal is to perform correlation clustering under circumstances in w...
A new paradigm for online EH regeneration using Genetic Algorithms (GAs) called Competitive Runtime Reconfiguration (CRR) is developed where performance is assessed based upon a b...
Assessing the similarity between objects is a prerequisite for many data mining techniques. This paper introduces a novel approach to learn distance functions that maximizes the c...
Christoph F. Eick, Alain Rouhana, Abraham Bagherje...