This paper presents research results of our investigation of the imbalanced data problem in the classification of different types of weld flaws, a multi-class classification probl...
Seed sampling is critical in semi-supervised learning. This paper proposes a clusteringbased stratified seed sampling approach to semi-supervised learning. First, various clusteri...
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
When automatically extracting information from the world wide web, most established methods focus on spotting single HTMLdocuments. However, the problem of spotting complete web s...
Martin Ester, Hans-Peter Kriegel, Matthias Schuber...
Manual classification of free-text documents within a predefined hierarchy is highly time consuming. This is especially true for clinical guidelines, which are often indexed by mu...
Robert Moskovitch, Shiva Cohen-Kashi, Uzi Dror, If...