Relationships Between Efficiency and Execution Time of Full Multigrid Methods on Parallel Computers
IEEE Transactions on Parallel and Distributed Systems
Biclustering of Expression Data
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
The maximum edge biclique problem is NP-complete
Discrete Applied Mathematics
A novel evolutionary data mining algorithm with applications to churn prediction
IEEE Transactions on Evolutionary Computation
Analysis of crossovers and selections in a coarse-grained parallel genetic algorithm
Mathematical and Computer Modelling: An International Journal
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One of the main challenges in data analytics is that discovering structures and patterns in complex datasets is a computer-intensive task. Recent advances in high-performance computing provide part of the solution. Multicore systems are now more affordable and more accessible. In this paper, we investigate how this can be used to develop more advanced methods for data analytics. We focus on two specific areas: model-driven analysis and data mining using optimisation techniques.