In this paper, a new selective sampling method for the active learning framework is presented. Initially, a small training set ? and a large unlabeled set ? are given. The goal is...
The problem of time series classification has attracted great interest in the last decade. However current research assumes the existence of large amounts of labeled training data...
—Significant research has been done on recognizing the daily activities using acceleration data but few works have focused on classifying the movements comprising an activity du...
Subgraph patterns are widely used in graph classification, but their effectiveness is often hampered by large number of patterns or lack of discrimination power among individual p...
A mainstay in cancer diagnostics is the classification or grading of cell nuclei based on their appearance. While the analysis of cytological samples has been automated successful...
Eric Cosatto, Matthew Miller, Hans Peter Graf, Joh...