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, ...
—Learning ontology from text is a challenge in knowledge engineering research and practice. Learning relations between concepts is even more difficult work. However, when conside...
Machine learning is a key technology to design and create intelligent systems, products, and related services. Like many other design departments, we are faced with the challenge t...
Bram van der Vlist, Rick van de Westelaken, Christ...
Abstract. In preference learning, the algorithm observes pairwise relative judgments (preference) between items as training data for learning an ordering of all items. This is an i...
Related objects may look similar at low-resolutions; differences begin to emerge naturally as the resolution is increased. By learning across multiple resolutions of input, knowle...