Voir la notice de l'article provenant de la source Math-Net.Ru
@article{MZM_2006_80_6_a14, author = {Yu. V. Malykhin}, title = {Local entropy in learning theory}, journal = {Matemati\v{c}eskie zametki}, pages = {946--949}, publisher = {mathdoc}, volume = {80}, number = {6}, year = {2006}, language = {ru}, url = {http://geodesic.mathdoc.fr/item/MZM_2006_80_6_a14/} }
Yu. V. Malykhin. Local entropy in learning theory. Matematičeskie zametki, Tome 80 (2006) no. 6, pp. 946-949. http://geodesic.mathdoc.fr/item/MZM_2006_80_6_a14/
[1] R. DeVore, G. Kerkyacharian, D. Picard, V. Temlyakov, “Mathematical methods for supervised learning”, IMI Preprints, 22, 2004, 51 pp.
[2] Y. Yang, A. Barron, Ann. of Statist., 27:5 (1999), 1564–1599 | DOI | MR | Zbl
[3] V. Temlyakov, “Approximation in learning theory”, IMI Preprints, 5, 2005, 44 pp.
[4] V. Temlyakov, “Optimal estimators in learning theory”, IMI Preprints, 23, 2004, 29 pp.