In this paper we describe the parallelization of two nearest neighbour classification algorithms. Nearest neighbour methods are well-known machine learning techniques. They have be...
The increasing availability of interaction graphs requires new resource-efficient tools capable of extracting valuable biological knowledge from these networks. In this paper we ...
Discovering patterns or frequent episodes in transactions is an important problem in data-mining for the purpose of infering deductive rules from them. Because of the huge size of...
This paper presents provable work-optimal parallelizations of STL (Standard Template Library) algorithms based on the workstealing technique. Unlike previous approaches where a deq...
We present in detail a GCA (Global Cellular Automaton) algorithm with 3n cells for Hirschberg’s algorithm which determines the connected components of a n-node undirected graph w...