We discuss the problem of clustering elements according to the sources that have generated them. For elements that are characterized by independent binary attributes, a closedform...
We consider visual category recognition in the framework of measuring similarities, or equivalently perceptual distances, to prototype examples of categories. This approach is qui...
Alexander C. Berg, Hao Zhang 0003, Jitendra Malik,...
In this work we propose an approach to binary classification based on an extension of Bayes Point Machines. Particularly, we take into account the whole set of hypotheses that are...
We have developed a machine learning toolbox, called SHOGUN, which is designed for unified large-scale learning for a broad range of feature types and learning settings. It offers...
We introduce three ensemble machine learning methods for analysis of biological DNA binding by transcription factors (TFs). The goal is to identify both TF target genes and their ...