http://dx.doi.org/10.5755/j01.itc.44.2.6723. Abstract. In this paper, we develop efficient parallel algorithms for the statistical processing of large data ...
Jun 25, 2015 · This research demonstrates that the application of modern parallel technologies allows a fast and accurate estimation of mixed-stable parameters ...
Nov 5, 2018 · In this paper, we develop efficient parallel algorithms for the statistical processing of large data sets. Namely, we parallelize the ...
In this study, we propose a parallel programming method for linear mixed models (LMM) generated from big data.
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Sep 1, 2020 · In this study, we propose a parallel programming method for linear mixed models (LMM) generated from big data. A commonly used algorithm ...
Jun 11, 2021 · Mixed-stable models for 29 DAX companies are constructed employing efficient parallel algorithms for the processing of long-term data series.
In this research, we develop and expand our parallel computing approach [2] to the mixed-stable modelling [4] of high-frequency data. A summary of the ...
Apr 30, 2024 · In particular, standard linear model methods cannot account for the covariance and grouping structures present in large datasets, and the ...
A review on large-scale data processing with parallel and distributed randomized extreme learning machine neural networks.
Aug 16, 2024 · Parallel architectures and programming models are crucial for high-performance computing. They enable efficient use of multiple processors ...