Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
One of the main reasons for using parallel evolutionary algorithms (PEAs) is to obtain efficient algorithms with an execution time much lower than that of their sequential counter...
The Lov´asz Local Lemma is a tool that enables one to show that certain events hold with positive, though very small probability. It often yields existence proofs of results with...
We argue in this paper that benchmarking should be complemented by direct measurement of parallelisation overheads when evaluating parallel state-space exploration algorithms. Thi...
Abstract: In this paper, we present a new, easy to implement algorithm for detecting the termination of a parallel asynchronous computation on distributedmemory MIMD computers. We ...
Allison H. Baker, Silvia A. Crivelli, Elizabeth R....