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@article{INTO_2019_166_a9, author = {Z. M. Shibzukhov}, title = {Minimizing robust estimates of sums of parameterized functions}, journal = {Itogi nauki i tehniki. Sovremenna\^a matematika i e\"e prilo\v{z}eni\^a. Temati\v{c}eskie obzory}, pages = {95--109}, publisher = {mathdoc}, volume = {166}, year = {2019}, language = {ru}, url = {http://geodesic.mathdoc.fr/item/INTO_2019_166_a9/} }
TY - JOUR AU - Z. M. Shibzukhov TI - Minimizing robust estimates of sums of parameterized functions JO - Itogi nauki i tehniki. Sovremennaâ matematika i eë priloženiâ. Tematičeskie obzory PY - 2019 SP - 95 EP - 109 VL - 166 PB - mathdoc UR - http://geodesic.mathdoc.fr/item/INTO_2019_166_a9/ LA - ru ID - INTO_2019_166_a9 ER -
%0 Journal Article %A Z. M. Shibzukhov %T Minimizing robust estimates of sums of parameterized functions %J Itogi nauki i tehniki. Sovremennaâ matematika i eë priloženiâ. Tematičeskie obzory %D 2019 %P 95-109 %V 166 %I mathdoc %U http://geodesic.mathdoc.fr/item/INTO_2019_166_a9/ %G ru %F INTO_2019_166_a9
Z. M. Shibzukhov. Minimizing robust estimates of sums of parameterized functions. Itogi nauki i tehniki. Sovremennaâ matematika i eë priloženiâ. Tematičeskie obzory, Proceedings of the IV International Scientific Conference "Actual Problems of Applied Mathematics". Kabardino-Balkar Republic, Nalchik, Elbrus Region, May 22–26, 2018. Part II, Tome 166 (2019), pp. 95-109. http://geodesic.mathdoc.fr/item/INTO_2019_166_a9/
[1] Khyuber P., Robastnost v statistike, M., 1984 | MR
[2] Shibzukhov Z. M., “Agregiruyuschie korrektnye operatsii nad algoritmami”, Dokl. RAN., 91:3 (2015), 391–393 | MR | Zbl
[3] Beliakov G., Kelarev A., Yearwood J., Robust artificial neural networks and outlier detection, arXiv: 1110.0169v1 [math.OC]
[4] Beliakov G. , Sola H., Calvo T., A Practical Guide to Averaging Functions, Springer, 2016 | MR
[5] Calvo T., Beliakov G., “Aggregation functions based on penalties”, Fuzzy Sets Syst., 161:10 (2010), 1420–1436 | DOI | MR | Zbl
[6] Grabich M., Marichal J.-L., Pap E., Aggregation Functions, Cambridge Univ. Press, Cambridge, 2009 | MR
[7] Huber P. J., Robust Statistics, Wiley, New York, 1981 | MR | Zbl
[8] Knigma D. P., Ba J., Adam: A Method for Stochastic Optimization, arXiv: 1412.6980 [cs.LG] | MR
[9] Koenker R., Quantile regression, Campridge Univ. Press, New York, 2005 | MR | Zbl
[10] Ma Y., Li L., Huang X., Wang S., “Robust support vector machine using least median loss penalty”, IFAC Proc. Vols., 44:1 (2011), 11208–11213 | DOI
[11] Mesiar R., Komornikova M., Kolesarova A., Calvo T., “Aggregation functions: A revision”, Fuzzy Sets and Their Extensions: Representation, Aggregation and Models, eds. Bustince H., Herrera F., Montero J., Springer, Berlin–Heidelberg, 2008 | MR | Zbl
[12] Newey W., Powell J., “Asymmetric least squares estimation and testing”, Econometrica., 55:4 (1987), 819–847 | DOI | MR | Zbl
[13] Rousseeuw P. J., “Least median of squares regression”, J. Am. Stat. Ass., 1984, no. 79, 871–880 | DOI | MR | Zbl
[14] Rousseeuw P. J., Leroy A. M., Robust regression and outlier detection, Wiley, New York, 1987 | MR | Zbl
[15] Schmidt M., Le Roux N., Bach F., “Minimizing finite sums with the stochastic average gradient”, Math. Program., 162:1-2 (2017), 83–112 | DOI | MR | Zbl
[16] Shibzukhov Z. M., “Correct aggregate operations with algorithms”, Pattern Recogn. Image Anal., 24:3 (2014), 377–382 | DOI
[17] Shibzukhov Z. M., “On the principle of empirical risk minimization based on averaging aggregation functions”, Dokl. Math., 96:2 (2017), 494–497 | DOI | MR | Zbl
[18] Vapnik V., The Nature of Statistical Learning Theory, Springer-Verlag, 2000 | MR | Zbl
[19] Yohai V. J., “High breakdown-point and high effciency robust estimates for regression”, Ann. Stat., 1987, no. 15, 642–656 | DOI | MR | Zbl