Geodesic
Effectiveness estimation of matrices compression in the procedures of randomized machine learning
Informacionnye tehnologii i vyčislitelnye sistemy, no. 1 (2018), pp. 3-7.

Voir la notice de l'article provenant de la source Math-Net.Ru

The method of estimation effectiveness of the matrices compressions. That oriented to the procedures randomized machine learning. It is proposed to measure of effectiveness in the term of the Kullback-Leibler function.
Keywords: randomized machine learning, entropy, KL-distance. 
@article{ITVS_2018_1_a0,
     author = {Yu. S. Popkov},
     title = {Effectiveness estimation of matrices compression in the procedures of randomized machine learning},
     journal = {Informacionnye tehnologii i vy\v{c}islitelnye sistemy},
     pages = {3--7},
     publisher = {mathdoc},
     number = {1},
     year = {2018},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/ITVS_2018_1_a0/}
}
TY  - JOUR
AU  - Yu. S. Popkov
TI  - Effectiveness estimation of matrices compression in the procedures of randomized machine learning
JO  - Informacionnye tehnologii i vyčislitelnye sistemy
PY  - 2018
SP  - 3
EP  - 7
IS  - 1
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/ITVS_2018_1_a0/
LA  - ru
ID  - ITVS_2018_1_a0
ER  - 
%0 Journal Article
%A Yu. S. Popkov
%T Effectiveness estimation of matrices compression in the procedures of randomized machine learning
%J Informacionnye tehnologii i vyčislitelnye sistemy
%D 2018
%P 3-7
%N 1
%I mathdoc
%U http://geodesic.mathdoc.fr/item/ITVS_2018_1_a0/
%G ru
%F ITVS_2018_1_a0
Yu. S. Popkov. Effectiveness estimation of matrices compression in the procedures of randomized machine learning. Informacionnye tehnologii i vyčislitelnye sistemy, no. 1 (2018), pp. 3-7. http://geodesic.mathdoc.fr/item/ITVS_2018_1_a0/