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Affine-Invariant Ensemble Transform Methods for Logistic Regression

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Bibliographic Details
Main Authors: Jakiw, Pidstrigach, Sebastian, Reich
Format: Book
Language:English
Published: Springer 2023
Subjects:
well-established homotopy
logistic regression problems
Online Access:https://link.springer.com/article/10.1007/s10208-022-09550-2
https://dlib.phenikaa-uni.edu.vn/handle/PNK/7425
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spelling oai:localhost:PNK-74252023-04-03T03:58:23Z Affine-Invariant Ensemble Transform Methods for Logistic Regression Jakiw, Pidstrigach Sebastian, Reich well-established homotopy logistic regression problems CC BY We investigate the application of ensemble transform approaches to Bayesian inference of logistic regression problems. Our approach relies on appropriate extensions of the popular ensemble Kalman filter and the feedback particle filter to the cross entropy loss function and is based on a well-established homotopy approach to Bayesian inference. The arising finite particle evolution equations as well as their mean-field limits are affine-invariant. Furthermore, the proposed methods can be implemented in a gradient-free manner in case of nonlinear logistic regression and the data can be randomly subsampled similar to mini-batching of stochastic gradient descent. 2023-04-03T03:58:23Z 2023-04-03T03:58:23Z 2022 Book https://link.springer.com/article/10.1007/s10208-022-09550-2 https://dlib.phenikaa-uni.edu.vn/handle/PNK/7425 en application/pdf Springer
institution Digital Phenikaa
collection Digital Phenikaa
language English
topic well-established homotopy
logistic regression problems
spellingShingle well-established homotopy
logistic regression problems
Jakiw, Pidstrigach
Sebastian, Reich
Affine-Invariant Ensemble Transform Methods for Logistic Regression
description CC BY
format Book
author Jakiw, Pidstrigach
Sebastian, Reich
author_facet Jakiw, Pidstrigach
Sebastian, Reich
author_sort Jakiw, Pidstrigach
title Affine-Invariant Ensemble Transform Methods for Logistic Regression
title_short Affine-Invariant Ensemble Transform Methods for Logistic Regression
title_full Affine-Invariant Ensemble Transform Methods for Logistic Regression
title_fullStr Affine-Invariant Ensemble Transform Methods for Logistic Regression
title_full_unstemmed Affine-Invariant Ensemble Transform Methods for Logistic Regression
title_sort affine-invariant ensemble transform methods for logistic regression
publisher Springer
publishDate 2023
url https://link.springer.com/article/10.1007/s10208-022-09550-2
https://dlib.phenikaa-uni.edu.vn/handle/PNK/7425
_version_ 1762184302615855104
score 8.891145

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