Existing work for query processing over graph data models often relies on pre-computing the transitive closure or path indexes. In this paper, we propose a family of stack-based a...
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,...
Syntactic word reordering is essential for translations across different grammar structures between syntactically distant languagepairs. In this paper, we propose to embed local a...
Electronic Prognostics (EP) is a technique used in high-reliability and high-availability systems to actively and proactively detect faults, allowing the reduction of system downt...
The usual data mining setting uses the full amount of data to derive patterns for different purposes. Taking cues from machine learning techniques, we explore ways to divide the d...