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This article is cited in 2 scientific papers (total in 2 papers)
Optimization, System Analysis, and Operations Research
Entropy-randomized projection
Yu. S. Popkovab, Yu. A. Dubnovac, A. Yu. Popkova a Federal Research Center “Computer Science and Control,”
Russian Academy of Sciences, Moscow, 119333 Russia
b Trapeznikov Institute of Control Sciences, Russian Academy of Sciences, Moscow, 117997 Russia
c National Research University Higher School of Economics, Moscow, 101000 Russia
Abstract:
We propose a new randomized projection method based on entropy optimization of random projection matrices (the ERP method). The concept of compactness indicator of a data matrix, which is stored in projection matrices, is introduced. An ERP algorithm is formulated in the form of a conditional maximization problem for an entropy functional defined on the probability density functions of the projection matrices. A discrete version of this problem is considered, and conditions are obtained for the existence and uniqueness of its positive solution. Procedures are developed for the implementation of entropy-optimal projection matrices by sampling the probability density functions.
Keywords:
random projection, compression and expansion of data matrix, projection matrix, compactness indicator, density function sampling, variance set, interquartile set.
Citation:
Yu. S. Popkov, Yu. A. Dubnov, A. Yu. Popkov, “Entropy-randomized projection”, Avtomat. i Telemekh., 2021, no. 3, 149–168; Autom. Remote Control, 82:3 (2021), 490–505
Linking options:
https://www.mathnet.ru/eng/at15516 https://www.mathnet.ru/eng/at/y2021/i3/p149
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Abstract page: | 224 | Full-text PDF : | 14 | References: | 30 | First page: | 20 |
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