Optimal subsampling for softmax regression

Author: rptl

August undefined, 2024

WebSubsampling is an efﬁcient method to deal with massive data. In this paper, we inves-tigate the optimal subsampling for linear quantile regression when the covariates are functions. The asymptotic distribution of the subsampling estimator is ﬁrst derived. Then, we obtain the optimal subsampling probabilities based on the A-optimality cri ... WebDec 18, 2024 · To meet the challenge of massive data, Wang et al. (J Am Stat Assoc 113(522):829–844, 2024b ) developed an optimal subsampling method for logistic …

Optimal subsampling for softmax regression - Research …

WebJul 21, 2024 · We investigate optimal subsampling for quantile regression. We derive the asymptotic distribution of a general subsampling estimator and then derive two versions … WebThis paper fills the gap by studying the subsampling method for a widely used missing data estimator, the augmented inverse probability weighting (AIPW) estimator. The response mean estimation problem with missing responses is discussed for illustration. A two-stage subsampling method is proposed via Poisson sampling framework. how many highlights can you have on instagram

Optimal subsampling for softmax regression SpringerLink

WebLightGBM LightGBM（Light Gradient Boosting Machine）是一个基于梯度提升决策树（GBDT）的高效机器学习框架。它是由微软公司开发的，旨在提供更快、更高效的训练和预测性能。LightGBM在许多数据科学竞赛中都表现出色&am… WebJan 28, 2024 · The optimal subsampling methods have been investigated to include logistic regression models, softmax regression models, generalized linear models, quantile … WebApr 21, 2009 · The model is an extension of the clustered ordinal regression approach of Hedeker and Gibbons that includes the continuous outcome. To handle subsampling, we then derive a partial likelihood (PL) that is based on the bivariate model, and we give an expression for the PL score in Section 3. We show that consistent estimates can be … how accurate is zillow reddit

Optimal subsampling for softmax regression - Research …

Scilit Article - Optimal subsampling for softmax regression

WebSubsampling techniques are efficient methods for handling big data. Quite a few optimal sampling methods have been developed for parametric models in which the loss … WebMar 25, 2024 · We investigate optimal subsampling for quantile regression. We derive the asymptotic distribution of a general subsampling estimator and then derive two versions of optimal subsampling … Expand. 59. PDF. Save. Alert. Optimal Sampling for Generalized Linear Models Under Measurement Constraints. Tao Zhang, Y. Ning, D. Ruppert; how accurate is zestimate 2022WebOptimal Subsampling for Softmax Regression 3 2 Model setup and optimal subsampling. Yaqiong Yao, Haiying Wang. Published 2024. Mathematics. To meet the challenge of … how accurate is zestimate vs appraisal

"WebThe problem of variable selection in neural network regression models with dependent data is considered. In this framework, a test procedure based on the introduction of a measure for the variable re " - Optimal subsampling for softmax regression

Optimal subsampling for softmax regression

[PDF] Optimal subsampling designs Semantic Scholar

WebFor softmax regression, the optimal subsampling algorithm has been investigated in Yao and Wang (2024) under the baseline constraint, where one dimension of the multivariate … WebThe increasing volumes of data bring new challenges for parameter estimation in softmax regression, and the optimal subsampling method is an effective way to solve them. …

Did you know?

WebThe purpose of this paper is to extend their method to softmax regression, which is also called multinomial logistic regression and is commonly used to model data with multiple … WebDec 1, 2024 · Wang H Ma Y Optimal subsampling for quantile regression in big data Biometrika 2024 108 1 99 112 4226192 10.1093/biomet/asaa043 1462.62248 Google Scholar; Wang H Zhu R Ma P Optimal subsampling for large sample logistic regression J. Am. Stat. Assoc. 2024 113 522 829 844 3832230 10.1080/01621459.2024.1292914 …

WebApr 6, 2024 · The theory encompasses and generalises most existing methods in the field of optimal subdata selection based on unequal probability sampling and inverse probability weighting, and derives optimality conditions for a general class of optimality criteria. Subsampling is commonly used to overcome computational and economical bottlenecks … WebMar 17, 2024 · This article focuses on quantile regression with massive data where the sample size n (greater than 1 0 6 in general) is extraordinarily large but the dimension d (smaller than 20 in general) is small. We first formulate the general subsampling procedure and establish the asymptotic property of the resultant estimator.

http://geekdaxue.co/read/johnforrest@zufhe0/qdms71 WebOptimal subsampling for softmax regression Article Full-text available Apr 2024 Yaqiong Yao Haiying Wang To meet the challenge of massive data, Wang et al. (J Am Stat Assoc 113 (522):829–844,...

WebNov 5, 2024 · Title: Optimal Poisson Subsampling for Softmax Regression Authors: Yaqiong Yao, Jiahui Zou Award ID(s): 2105571 Publication Date: 2024-11-05 NSF-PAR ID: …

Web844, 2024b) developed an optimal subsampling method for logistic regression. The purpose of this paper is to extend their method to softmax regression, which is also called … how many highlander moviesWebMar 12, 2024 · The key idea of subsampling is to perform statistical analysis on a representative subsample drawn from the full data. It provides a practical solution to … how many high school application in nyc 2022WebDec 4, 2024 · This thesis is concerned with massive data analysis via robust A-optimally efficient non-uniform subsampling. Motivated by the fact that massive data often contain outliers and that uniform sampling is not efficient, we give numerous sampling distributions by minimizing the sum of the component variances of the subsampling estimate. And … how many highlander movies were thereWebSep 17, 2015 · On the basis of the criterion, we provide two novel subsampling methods, the optimal subsampling and the predictor- length subsampling methods. The predictor … how many highlander films are thereWebApr 6, 2024 · Rogers, Steven C. Youth Suicide is 100% Preventable: 4 Things Parents Need to Know CCMC Blog 02/25/2024 Carter EJ, Kaman K, Baron K, Miller M, Krol DM, Harpalani D, Aseltine RH, Pagoto S. (2024) Parent-reported penicillin allergies in children: A qualitative study.Am J Infect Control. Jan;51(1):56-61. doi: 10.1016/j.ajic.2024.04.008. Epub 2024 … how many high school age children in usWebThis idea was generalized in [11] to softmax regression. An optimal subsampling method under the A-optimality criterion (OSMAC) for logistic re-gression inspired by the idea of optimal design of experiments was developed in [12]. They proposed to use a pilot subsample to estimate the optimal subsampling probabilities, which how accurate is zestimateWebFor softmax regression, the optimal subsampling algorithm has been investigated in [1] under the baseline constraint, where one dimension of the multivariate response variable … how many highlights can you have on twitch