Abstract
This chapter presents the parallel version of Pareto optimization algorithm, PPOSS, for subset selection. We disclose that the parallelization does not break the effectiveness of Pareto optimization while reducing the total time. Moreover, given sufficient processors, PPOSS can be both faster and more accurate than parallel greedy methods. The efficiency and the effectivenss of PPOSS is also verified in machine learning tasks.
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© 2019 Springer Nature Singapore Pte Ltd.
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Zhou, ZH., Yu, Y., Qian, C. (2019). Subset Selection: Acceleration. In: Evolutionary Learning: Advances in Theories and Algorithms. Springer, Singapore. https://doi.org/10.1007/978-981-13-5956-9_18
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DOI: https://doi.org/10.1007/978-981-13-5956-9_18
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Publisher Name: Springer, Singapore
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Online ISBN: 978-981-13-5956-9
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