We present the notion of Ranking for evaluation of two-class classifiers. Ranking is based on using the ordering information contained in the output of a scoring model, rather tha...
In this paper, we address the problems of adaptive schema mappings between different peers in peer-to-peer network and searching for interesting data residing at different peers ba...
For unsupervised clustering in a network of spiking neurons we develop a temporal encoding of continuously valued data to obtain arbitrary clustering capacity and precision with a...
When data instances are inter-related, as are nodes in a social network or hyperlink graph, algorithms for collective classification (CC) can significantly improve accuracy. Recen...
The Passive Aggressive framework [1] is a principled approach to online linear classification that advocates minimal weight updates i.e., the least required so that the current tr...