Building adaptive constraint solvers is a major challenge in constraint programming. An important line of research towards this goal is concerned with ways to dynamically adapt th...
Dealing with numerical information is practically important in many real-world planning domains where the executability of an action can depend on certain numerical conditions, an...
Background: The ability to visualize genomic features and design experimental assays that can target specific regions of a genome is essential for modern biology. To assist in the...
GENET is a heuristic repair algorithm which demonstrates impressive e ciency in solving some large-scale and hard instances of constraint satisfaction problems (CSPs). In this pap...
Kenneth M. F. Choi, Jimmy Ho-Man Lee, Peter J. Stu...
Naive Bayes is one of the most efficient and effective inductive learning algorithms for machine learning and data mining. Its competitive performance in classification is surpris...