We identify a new and important global (or nonbinary) constraint which ensures that the values taken by two vectors of variables, when viewed as multisets, are ordered. This const...
Alan M. Frisch, Ian Miguel, Zeynep Kiziltan, Brahi...
Different qualitative models have been proposed for decision under uncertainty in Artificial Intelli gence, but they generally fail to satisfy the princi ple of strict Pareto ...
Refinement operators for theories avoid the problems related to the myopia of many relational learning algorithms based on the operators that refine single clauses. However, the n...
Nicola Fanizzi, Stefano Ferilli, Nicola Di Mauro, ...
Most recent research of scalable inductive learning on very large dataset, decision tree construction in particular, focuses on eliminating memory constraints and reducing the num...
Noun compound interpretation is the task of determining the semantic relations among the constituents of a noun compound. For example, "concrete floor" means a floor mad...
With the proliferation of heterogeneous devices (desktop computers, personal digital assistants, phones), multimedia documents must be played under various constraints (small scre...
In this paper we propose the framework of Monte Carlo algorithms as a useful one to analyze ensemble learning. In particular, this framework allows one to guess when bagging will ...