In this paper, we propose a parallel algorithm for mining maximal frequent itemsets from databases. A frequent itemset is maximal if none of its supersets is frequent. The new par...
Abstract. Many large-scale optimization problems rely on graph theoretic solutions; yet high-performance computing has traditionally focused on regular applications with high degre...
The development of efficient parallel algorithms for large scale wildfire simulations is a challenging research problem because the factors that determine wildfire behavior are com...
We construct parallel algorithms with implementations to solve the clique problem in practice and research their computing time compared with sequential algorithms. The parallel a...
Holger Blaar, Thomas Lange, Renate Winter, Marcel ...
— The Parallel Resource-Optimal (PRO) computation model was introduced by Gebremedhin et al. [2002] as a framework for the design and analysis of efficient parallel algorithms. ...
A motion panorama is an efficient and compact representation of the underlying video. However, the motion panorama construction process is computationally intensive and hence extr...
Yong Wei, Hongyu Wang, Suchendra M. Bhandarkar, Ka...
In this work we present a parallel algorithm for the solution of a least squares problem with structured matrices. This problem arises in many applications mainly related to digit...
Pedro Alonso, Antonio M. Vidal, Alexey L. Lastovet...
For many application-level distributed protocols and parallel algorithms, the set of participants, the number of messages or the interaction structure are only known at run-time. T...
Abstract. Until recently algorithms continuously gained free performance improvements due to ever increasing processor speeds. Unfortunately, this development has reached its limit...
The computation of covariance and correlation matrices are critical to many data mining applications and processes. Unfortunately the classical covariance and correlation matrices...
James Chilson, Raymond T. Ng, Alan Wagner, Ruben H...