Many of today's CBR systems are passive in nature: they require human users to activate them manually and to provide information about the incoming problem explicitly. In this...
A new approach to ensemble learning is introduced that takes ranking rather than classification as fundamental, leading to models on the symmetric group and its cosets. The approa...
A labeled sequence data set related to a certain biological property is often biased and, therefore, does not completely capture its diversity in nature. To reduce this sampling b...
This study investigates Bayes classification of online Arabic characters using histograms of tangent differences and Gibbs modeling of the class-conditional probability density fun...
We present a framework for margin based active learning of linear separators. We instantiate it for a few important cases, some of which have been previously considered in the lite...
Maria-Florina Balcan, Andrei Z. Broder, Tong Zhang