0583574 20240402215301.520240305235959.9 85174447437 001155257400031 10.1007/978-3-031-42508-0_31 On the Bayesian Interpretation of Penalized Statistical Estimators 10 s. P cav_un_epca*0579679978-3-031-42507-3Artificial Intelligence and Soft Computing. 22nd International Conference, ICAISC 2023, Proceedings, Part 2343-352ChamSpringer2023RutkowskiL.SchererR.KorytkowskiM.PedryczW.TadeusiewiczR.ZuradaJ. M. Bayesian estimation regularization penalization robustness regression cav_un_auth*0345793 Kalina Jan UTIA-B Stochastická informatika Department of Stochastic Informatics SI SI Department of Stochastic Informatics Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0353498 Peštová B. CZ http://library.utia.cas.cz/separaty/2023/SI/kalina-0583574.pdf GA21-05325S GA ČR cav_un_auth*0409039 The aim of this work is to search for intuitive interpretations of penalized statistical estimators. Penalized estimates of the parameters of three models obtained by Bayesian reasoning are explained here to correspond to the intuition. First, the paper considers Bayesian estimates of the mean and covariance matrix for the multivariate normal distribution. Second, a connection of a robust regularized version of Mahalanobis distance with Bayesian estimation is discussed. Third, regularization networks, which represent a common nonparametric tool for regression modeling, are presented as Bayesian methods as well. On the whole, selected important multivariate and/or regression models are considered and novel interpretations are formulated. cav_un_auth*0460088 ICAISC 2023: International Conference on Artificial Intelligence and Soft Computing /22./ 20230718 20230722 Zakopane PL BA 10000 10100 10103 2024 PR RVO:67985556 https://hdl.handle.net/11104/0351579 S Proceedings Paper Computer Science Artificial Intelligence|Computer Science Theory Methods 2023 85174447437 SCOPUS PUBMED 001155257400031 WOS cav_un_epca*0579679 Artificial Intelligence and Soft Computing. 22nd International Conference, ICAISC 2023, Proceedings, Part 2 Springer 2023 Cham 343 352 978-3-031-42507-3 Lecture Notes in Computer Science 14126 Rutkowski L. 340 Scherer R. 340 Korytkowski M. 340 Pedrycz W. 340 Tadeusiewicz R. 340 Zurada J. M. 340