The goal of multi-objective clustering (MOC) is to decompose a dataset into similar groups maximizing multiple objectives in parallel. In this paper, we provide a methodology, arch...
Rachsuda Jiamthapthaksin, Christoph F. Eick, Ricar...
Abstract. There exist numerous algorithms that cluster data-points from largescale genomic experiments such as sequencing, gene-expression and proteomics. Such algorithms may emplo...
Distributed-system observation tools require an efficient data structure to store and query the partial-order of execution. Such data structures typically use vector timestamps to...
Given the importance of parallel mesh generation in large-scale scientific applications and the proliferation of multilevel SMTbased architectures, it is imperative to obtain ins...
Christos D. Antonopoulos, Xiaoning Ding, Andrey N....
We introduce a parallel approximation of an Over-determined Laplacian Partial Differential Equation solver (ODETLAP) applied to the compression and restoration of terrain data use...
Jared Stookey, Zhongyi Xie, Barbara Cutler, W. Ran...