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, ...
Highly heterogeneous XML data collections that do not have a global schema, as arising, for example, in federations of digital libraries or scientific data repositories, cannot be...
Abstract. One solution to the lack of label problem is to exploit transfer learning, whereby one acquires knowledge from source-domains to improve the learning performance in the t...
Peer review meetings (PRMs) are formal meetings during which peers systematically analyze artifacts to improve their quality and report on non-conformities. This paper presents an...
Patrick d'Astous, Pierre N. Robillard, Franç...
Evaluating pixel shaders consumes a growing share of the computational budget for real-time applications. However, the significant temporal coherence in visible surface regions, ...
Diego F. Nehab, Pedro V. Sander, Jason Lawrence, N...