High-dimensional generalized linear models
WebFebruary 2024 High dimensional generalized linear models for temporal dependent data. Yuefeng Han, Ruey S. Tsay, Wei Biao Wu. Author Affiliations + Bernoulli 29(1): 105-131 … Webboth linear and logistic high-dimensional regression models. 2.1 Estimation in high-dimensional regression For the high-dimensional linear model (1), a commonly used …
High-dimensional generalized linear models
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Web1 de set. de 2015 · Variable selection for high-dimensional generalized linear models with the weighted elastic-net procedure September 2015 Journal of Applied Statistics 43(5):1-14 Web1 de jul. de 2024 · Many current intrinsically interpretable machine learning models can only handle the data that are linear, low-dimensional, and relatively independent attributes and often with discrete attribute values, while the models that are capable of handling high-dimensional nonlinear data, like deep learning, have very poor interpretability.
WebA Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models. Part of Advances in Neural Information Processing Systems 35 (NeurIPS 2024) Main Conference Track. Bibtex Paper Supplemental. http://www-stat.wharton.upenn.edu/~tcai/paper/Transfer-Learning-GLM.pdf
WebAbstract. In this work, we study the transfer learning problem under high-dimensional generalized linear models (GLMs), which aim to improve the fit on target data by … http://www-stat.wharton.upenn.edu/~tcai/paper/html/Transfer-Learning-GLM.html
WebThe problem of obtaining an optimal spline with free knots is tantamount to minimizing derivatives of a nonlinear differentiable function over a Banach space on a compact …
Web3 de fev. de 2024 · Variable selection in a grouped manner is an attractive method since it respects the grouping structure in the data. In this paper, we study the adaptive group Lasso in the frame of high-dimensional generalized linear models. Both the number of groups diverging with the sample size and the number of groups exceeding the sample … can i buy a house with 716 credit scoreWeb19 de fev. de 2014 · We consider testing regression coefficients in high dimensional generalized linear models. An investigation of the test of Goeman et al. (2011) is … can i buy a house with a 500 credit scorefitness instructor courses corkWeb20 de fev. de 2014 · We consider testing regression coefficients in high dimensional generalized linear models. An investigation of the test of Goeman et al. (2011) is … can i buy a house with a 650 credit scoreWebWe study robust high-dimensional estimation of generalized linear models (GLMs); where a small number k of the n observations can be arbitrarily corrupted, and where the … can i buy a house with a 580 credit scoreWebAbstract. In this paper, we propose a sparse generalized linear model incorporating graphical structure among predictors (sGLMg), which is an extension of [37] where they exploit the structure information among predictors to improve the performance for the linear regression. There is an explicit expression between the coefficient and the ... fitness instructor courses kentWeb1 de jul. de 2024 · T-ridge estimator for generalized linear models. In this section, we exemplify the t-ridge estimator for maximum regularized likelihood estimation in generalized linear models. We consider data Z = ( y, X) that follow a conditional distribution (5) y i x i, β ∗ ∼ F with g ( E ( y i x i, β ∗)) = x i ⊤ β ∗. can i buy a house with a 600 credit score