We provide a principle for semi-supervised learning based on optimizing the rate of communicating labels for unlabeled points with side information. The side information is expres...
In this paper we introduce a new sparseness inducing prior which does not involve any (hyper)parameters that need to be adjusted or estimated. Although other applications are poss...
The choice of the kernel function is crucial to most applications of support vector machines. In this paper, however, we show that in the case of text classification, term-frequenc...
— This work shows comparatively the capacity of five Fuzzy Lattice Neurocomputing (FLN) classifiers. The mechanics of the five classifiers are illustrated geometrically on the pl...
Al Cripps, Vassilis G. Kaburlasos, Nghiep Nguyen, ...
Naive Bayes is an effective and efficient learning algorithm in classification. In many applications, however, an accurate ranking of instances based on the class probability is m...