ИНТЕЛЛЕКТУАЛЬНЫЕ СИСТЕМЫ И ТЕХНОЛОГИИ
Yu.S. Popkov Effectiveness estimation of matrices compression in the procedures of randomized machine learning
ВЫЧИСЛИТЕЛЬНЫЕ СИСТЕМЫ
РАСПОЗНАВАНИЕ ОБРАЗОВ
УПРАВЛЕНИЕ И ПРИНЯТИЕ РЕШЕНИЙ
Yu.S. Popkov Effectiveness estimation of matrices compression in the procedures of randomized machine learning

Abstract

The metod of estimation effectiveness of the matrices compressions? That oriented to the procedures ranomized machine learning. It is proposed to measure of effectiveness in the term of the Kullback-Leibler function.

Keywords:

randomized machine learning, entropy, KL-distance

pp. 3-7

References

1. Yu. S. Popkov, Yu. A. Dubnov, A. Yu. Popkov. Randomized Machine Learning: Statement, Solution, Applications //Proceedings of 2016 IEEE 8-th International Conference on Intelligent Systems (IS16). September 4-6, 2016. Sofia, Bulgaria, P.27-39.
2. Yuri S. Popkov, Zeev Volkovich, Yuri A. Dubnov, Renata Avros and Elena Ravve. // Entropy '2'-Soft Classification of Objects // Entropy, 2017, Vol. 19, Iss. 4, No.178.
3. Popkov Y.S., Dubnov Y.A. Entropy-robust randomized forecasting under small sets of retrospective data. Automation and Remote Control, 2016,v.77, No.5, p.839-854.
4. Bruckstein A.M., Donoho D.L., Elad M. From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals and Images. SIAM Rev. 2009, v.51, No.1, p.34-81.
5. Kendall M, Stewart A. Statisticheskie vivodi I sviazi, Nauka , 1973.
6. Jollife I.T. Principal Component Analysis. N.Y. Springer-Verlag, 2002.
7. Polyak B.T., Hlebnikov M.V. Metod glavnih komponent: robastnie versii // Avtomatika I telemehanika, 2017, №3, с.130-148.
8. Popkov Y.S. Entropiinii metod szhatia matric so sluchainimi znacheniami elemntov // ITVS, 2018, №1, с.
9. Kullback S., Leibler R.A. On information and Sufficiency. Ann. of Math. Statistics, 1951, v.22(1), p. 79-86.
10. Zhang Y., Li S., Wang T., Zhang Z. Divergence-based feature selection for separate classes. Neurocomputing, 2013, v.101, p. 32-42.

2018 / 02
2018 / 01
2017 / 04
2017 / 03

© ФИЦ ИУ РАН 2008-2018. Создание сайта "РосИнтернет технологии".