We study iterative randomized greedy algorithms for generating (elimination) orderings with small induced width and state space size - two parameters known to bound the complexity...
Kalev Kask, Andrew Gelfand, Lars Otten, Rina Decht...
The main objective of this paper is to provide a granular computing based interpretation of rules representing two levels of knowledge. This is done by adopting and adapting the de...
RecentlyFtwo new backtracking algorithmsF dynamic backtracking (DB)and partial order dynamicbacktracking (PDB) have been presented. These algorithms have the property to be additi...
Random forest induction is a bagging method that randomly samples the feature set at each node in a decision tree. In propositional learning, the method has been shown to work well...
Celine Vens, Anneleen Van Assche, Hendrik Blockeel...
The area of knowledge merging is concerned with merging conflicting information while preserving as much as possible. Most proposals in the literature work with knowledge bases exp...