We consider the problem of clustering data lying on multiple subspaces of unknown and possibly different dimensions. We show that one can represent the subspaces with a set of pol...
Prior knowledge, in the form of simple advice rules, can greatly speed up convergence in learning algorithms. Online learning methods predict the label of the current point and the...
Gautam Kunapuli, Kristin P. Bennett, Amina Shabbee...
Ensemble learning algorithms such as boosting can achieve better performance by averaging over the predictions of some base hypotheses. Nevertheless, most existing algorithms are ...
Motivation: Protein–protein complexes are known to play key roles in many cellular processes. However, they are often not accessible to experimental study because of their low s...
The problem of extracting a minimal number of data points from a large dataset, in order to generate a support vector machine (SVM) classifier, is formulated as a concave minimiza...