Abstract. We advocate to analyze the average complexity of learning problems. An appropriate framework for this purpose is introduced. Based on it we consider the problem of learni...
Statistical discrimination methods are suitable not only for classification but also for characterisation of differences between a reference group of patterns and the population u...
Carlos E. Thomaz, Nelson A. O. Aguiar, Sergio H. A...
We propose a unified manifold learning framework for semi-supervised and unsupervised dimension reduction by employing a simple but effective linear regression function to map the ...
Feiping Nie, Dong Xu, Ivor Wai-Hung Tsang, Changsh...
Social media are becoming increasingly popular and have attracted considerable attention from spammers. Using a sample of more than ninety thousand known spam Web sites, we found ...
Abstract. We propose an algorithm for Sparse Bayesian Classification for multi-class problems using Automatic Relevance Determination(ARD). Unlike other approaches which treat mult...