We study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for differ...
The objective of this work is to automatically detect the use of game bots in online games based on the trajectories of account users. Online gaming has become one of the most popu...
We address the problem of reasoning with instances of heterogeneously formalized ontologies. Given a set of semantic mappings, reconciling conceptual and instance level heterogenei...
Distributed Constraints Optimization (DCOP) is a powerful framework for representing and solving distributed combinatorial problems, where the variables of the problem are owned b...
Alon Grubshtein, Roie Zivan, Tal Grinshpoun, Amnon...
Classification has been commonly used in many data mining projects in the financial service industry. For instance, to predict collectability of accounts receivable, a binary clas...