Optimal subsampling for softmax regression
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. 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
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Websubsampling least squares regression. On the other hand, several scholars have developed optimal subsampling methods for parametric regression problems. For example, Wang et al. (2024a) proposed an inverse weighted subsampling method for logistic regression based on the A- or L-optimality criterion. Subsequently, a more efficient estimation WebApr 1, 2024 · They defined optimal subsampling probabilities by minimizing the asymptotic mean squared error (MSE) of the subsample-based estimator, and extracted sub-data …
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 … WebJan 28, 2024 · The optimal subsampling methods have been investigated to include logistic regression models, softmax regression models, generalized linear models, quantile …
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 … 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 …
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Weboped an optimal subsampling method for logistic regression. The purpose of this paper is to extend their method to softmax regression, which is also called multinomial logistic … can i bottle feed my newbornWebSubsampling 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 ... can i bottle my own watercan i bounce my newbornWebApr 25, 2024 · Softmax Regression Model; Image by Author. First, we have flattened our 28x28 image into a vector of length 784, represented by x in the above image. Second, we calculate the linear part for each class → zc = wc.X + bc where, zc is the linear part of the c’th class and wc is the set of weights of the c’th class. bc is the bias for the c ... can i box in my boilerWebFeb 1, 2024 · Furthermore, the optimal subsampling probabilities are derived according to the A-optimality criterion. It is shown that the estimator based on the optimal … can i box dye my hair lighterWebFor softmax regression, the optimal subsampling algorithm has been investigated in [1] under the baseline constraint, where one dimension of the multivariate response variable is set as the baseline and the corresponding parameter is set to be a vector of zeros. With this constraint, the resulting optimal subsampling probabilities treat the can i box after an low eyebrow incisionWebJul 21, 2024 · Two-step algorithm in implementing πLopt i. Step 1. Using the uniform sampling probability π0 i = 1 / N, draw a random subsample of size n0 to obtain a preliminary estimate of β, ˜β0. Replace β with ˜β0 in ( 8) to obtain the approximate optimal subsampling probabilities πLopt, ˜β0i. Step 2. fitness fanatic 意味