Selection of an optimal estimator typically relies on either supervised training samples (pairs of measurements and their associated true values), or a prior probability model for...
Machine learning often relies on costly labeled data, and this impedes its application to new classification and information extraction problems. This has motivated the developme...
Marco Gori Dipartimento di Ingegneria deU'Informazione Universita di Siena Via Roma 56 53100 Siena, Italy Alessandro Sperduti Dipartimento di Informatica Universita di Pisa C...
The relation between hard c-means (HCM), fuzzy c-means (FCM), fuzzy learning vector quantization (FLVQ), soft competition scheme (SCS) of Yair et al. (1992) and probabilistic Gaus...
We study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for differ...