We define and solve the problem of "distribution classification", and, in general, "distribution mining". Given n distributions (i.e., clouds) of multi-dimensi...
Yasushi Sakurai, Rosalynn Chong, Lei Li, Christos ...
We address the problem of efficiently learning Naive Bayes classifiers under classconditional classification noise (CCCN). Naive Bayes classifiers rely on the hypothesis that the ...
Proteomic profiling based on mass spectrometry is an important tool for studies at the protein and peptide level in medicine and health care. Thereby, the identification of releva...
Frank-Michael Schleif, Thomas Villmann, Barbara Ha...
We present a discriminative model that casts appearance modeling and visual matching into a single objective for visual tracking. Most previous discriminative models for visual tra...
Similarity search is a fundamental operation for applications that deal with unstructured data sources. In this paper we propose a new pivot-based method for similarity search, ca...