We study the problem of learning a classification task in which only a dissimilarity function of the objects is accessible. That is, data are not represented by feature vectors bu...
We address the problem of efficiently learning Naive Bayes classifiers under classconditional classification noise (CCCN). Naive Bayes classifiers rely on the hypothesis that the ...
Many biological propositions can be supported by a variety of different types of evidence. It is often useful to collect together large numbers of such propositions, together with...
Philip M. Long, Vinay Varadan, Sarah Gilman, Mark ...
Microcalcification (MC) clusters in mammograms can be an indicator of breast cancer. In this work we propose for the first time the use of support vector machine (SVM) learning fo...
Issam El-Naqa, Yongyi Yang, Miles N. Wernick, Niko...
Finding Contiguous Sequential Patterns (CSP) is an important problem in Web usage mining. In this paper we propose a new data structure, UpDown Tree, for CSP mining. An UpDown Tre...