Results 11 to 20 of about 61 (29)

Uniform convergence of adversarially robust classifiers

European Journal of Applied Mathematics
In recent years, there has been significant interest in the effect of different types of adversarial perturbations in data classification problems. Many of these models incorporate the adversarial power, which is an important parameter with an associated
Rachel Morris, Ryan Murray
doaj   +1 more source

On the existence of solutions to adversarial training in multiclass classification

European Journal of Applied Mathematics
Adversarial training is a min-max optimization problem that is designed to construct robust classifiers against adversarial perturbations of data. We study three models of adversarial training in the multiclass agnostic-classifier setting.
Nicolás García Trillos, Matt Jacobs, Jakwang Kim   +2 more
doaj   +1 more source

Estimation for spatial semi-functional partial linear regression model with missing response at random

Demonstratio Mathematica
The aim of this article is to study a semi-functional partial linear regression model (SFPLR) for spatial data with responses missing at random (MAR).
Benchikh Tawfik, Almanjahie Ibrahim M., Fetitah Omar, Attouch Mohammed Kadi   +3 more
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Level sets of depth measures in abstract spaces. [PDF]

Test (Madr), 2023
Cholaquidis A, Fraiman R, Moreno L.
europepmc   +1 more source

Robust analogs to the coefficient of variation. [PDF]

J Appl Stat, 2022
Arachchige CNPG, Prendergast LA, Staudte RG.   +2 more
europepmc   +1 more source

Robust and efficient estimation of GARCH models based on Hellinger distance. [PDF]

J Appl Stat, 2022
Zhao Q, Chen L, Wu J.
europepmc   +1 more source

Robust and efficient estimation of nonparametric generalized linear models. [PDF]

Test (Madr), 2023
Kalogridis I, Claeskens G, Van Aelst S.
europepmc   +1 more source

Robust fitting of mixtures of GLMs by weighted likelihood. [PDF]

Adv Stat Anal, 2022
Greco L.
europepmc   +1 more source

Depth functions and mutidimensional medians on minimal spanning trees. [PDF]

J Appl Stat, 2020
Yang M, Modarres R, Guo L.
europepmc   +1 more source

OPTIMAL DESIGNS FOR SPLINE WAVELET REGRESSION MODELS. [PDF]

J Stat Plan Inference, 2017
Maronge JM, Zhai Y, Wiens DP, Fang Z.
europepmc   +1 more source