Recommender systems based on collaborative filtering predict user preferences for products or services by learning past user-item relationships. A predominant approach to collabo...
Abstract. We address the issue of efficiently automating assume-guarantee reasoning for simulation conformance between finite state systems and specifications. We focus on a non...
Sagar Chaki, Edmund M. Clarke, Nishant Sinha, Pras...
This paper studies a novel paradigm for learning formal languages from positive and negative examples which consists of mapping strings to an appropriate highdimensional feature s...
The open nature of collaborative recommender systems present a security problem. Attackers that cannot be readily distinguished from ordinary users may inject biased profiles, deg...
Published as Technical Report LU-CS-TR:2005-238 on February 13, 2006, ISSN 1650-1276 Report 158, Lund University, Sweden 2006 We discuss and compare four fixed parameter algorithm...
Magdalene G. Borgelt, Christian Borgelt, Christos ...