Knowledge discovery in databases has become an increasingly important research topic with the advent of wide area network computing. One of the crucial problems we study in this p...
Personalized support for learners becomes even more important, when e-Learning takes place in open and dynamic learning and information networks. This paper shows how to realize p...
Peter Dolog, Nicola Henze, Wolfgang Nejdl, Michael...
Algorithms for learning the conditional probabilities of Bayesian networks with hidden variables typically operate within a high-dimensional search space and yield only locally op...
We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and sea...
Ioannis Tsamardinos, Laura E. Brown, Constantin F....
This paper proposes Noise-Direct, a design methodology for power integrity aware floorplanning, using microarchitectural feedback to guide module placement. Stringent power constr...
Fayez Mohamood, Michael B. Healy, Sung Kyu Lim, Hs...