Soft constraints extend classical constraints to deal with non-functional requirements, overconstrained problems and preferences. Bistarelli, Montanari and Rossi have developed a ...
Martin Wirsing, Grit Denker, Carolyn L. Talcott, A...
Gradient boosting is a flexible machine learning technique that produces accurate predictions by combining many weak learners. In this work, we investigate its use in two applica...
Bin Zhang, Abhinav Sethy, Tara N. Sainath, Bhuvana...
The criterion of total weighted completion time occurs as a sub-problem of combinatorial optimization problems in such diverse areas as scheduling, container loading and storage a...
We address the problem of approximate string matching in two dimensions, that is, to nd a pattern of size m m in a text of size n n with at most k errors (substitutions, insertions...
The maximal correlation problem (MCP) aiming at optimizing correlation between sets of variables plays a very important role in many areas of statistical applications. Currently, a...