This paper studies the problem of learning from ambiguous supervision, focusing on the task of learning semantic correspondences. A learning problem is said to be ambiguously supe...
In the last decade, connectionist models have been proposed that can process structured information directly. These methods, which are based on the use of graphs for the representa...
Werner Uwents, Gabriele Monfardini, Hendrik Blocke...
In this paper, we study the problem of learning a matrix W from a set of linear measurements. Our formulation consists in solving an optimization problem which involves regulariza...
Andreas Argyriou, Charles A. Micchelli, Massimilia...
The paper describes an ontology-based framework for bridging learning design and learning object content. In present solutions, researchers have proposed conceptual models and dev...
Abstract-- Nowadays, people are in need for continuous learning in order to keep up to date or to be upgraded in their job. An infrastructure for life-long learning requires contin...