Kernel coupling refers to the effect that kernel i has on kernel j in relation to running each kernel in isolation. The two kernels can correspond to adjacent kernels or a chain ...
Jonathan Geisler, Valerie E. Taylor, Xingfu Wu, Ri...
Methods for learning Bayesian networks can discover dependency structure between observed variables. Although these methods are useful in many applications, they run into computat...
Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller,...
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
al Partitioning by Predicate Abstraction and its Application to Data Warehouse Design Aleksandar Dimovski1 , Goran Velinov2 , and Dragan Sahpaski2 1 Faculty of Information-Communic...
Aleksandar Dimovski, Goran Velinov, Dragan Sahpask...
In this paper, we propose a novel personalized ranking system for amateur photographs. Although some of the features used in our system are similar to previous work, new features,...
Che-Hua Yeh, Yuan-Chen Ho, Brian A. Barsky, Ming O...