Results 71 to 80 of about 1,312,626 (282)
Bayesian Adaptive Lasso for Regression Models with Nonignorable Missing Responses
The main purpose of this article is to develop a Bayesian adaptive lasso procedure for analyzing linear regression models with nonignorable missing responses, in which the missingness mechanism is specified by a logistic regression model.
Yuanying Zhao, Xingde Duan
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Rod Origami (RodOri) springs harness snap‐through instabilities of pre‐stressed curved rods with geometrically programmable buckling behavior. Integrating RodOri springs with distinct geometries yields multistable metamaterials that undergo stepwise reconfiguration via sequential snapping, achieving wide‐range tunability of stiffness and resonance ...
Jeseung Lee +2 more
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Background There is increasing interest in examining the consequences of simultaneous exposures to chemical mixtures. However, a consensus or recommendations on how to appropriately select the statistical approach analyzing the health effects of mixture ...
Li Luo +3 more
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Intelligence quotient (IQ) is commonly measured in child development studies, while adaptive behavior is less frequently considered. Given its associations with functional outcomes in children with neurodevelopmental disabilities, adaptive behavior may ...
Shuting Zheng +7 more
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Through self‐supervised pretraining and supervised fine‐tuning on large‐scale cytology image datasets, CytoNet predicts lymph node metastasis and survival. Across independent cohorts, this multitask framework demonstrates robust performance, improves risk stratification beyond radiological assessment, and provides interpretable evidence to support ...
Guibin Hong +14 more
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Adaptive Lasso, Transfer Lasso, and Beyond: An Asymptotic Perspective [PDF]
This paper presents a comprehensive exploration of the theoretical properties inherent in the Adaptive Lasso and the Transfer Lasso. The Adaptive Lasso, a well-established method, employs regularization divided by initial estimators and is characterized ...
Fujisawa, Hironori, Takada, Masaaki
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Lassoed Forests: Random Forests with Adaptive Lasso Post-selection
Random forests are a statistical learning technique that use bootstrap aggregation to average high-variance and low-bias trees. Improvements to random forests, such as applying Lasso regression to the tree predictions, have been proposed in order to reduce model bias.
Jing Shang +3 more
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Upon UV irradiation, flexible and tough hydrogels are formed rapidly (>0.5 s) from dilute (>0.5 wt%) solutions of o‐ethylnitrobenzene–modified PVA. At ∼1.5 wt%, the hydrogels withstand up to 10 MPa compression, remain handleable even after 200‐fold swelling.
Masaaki Okihara +4 more
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The RNA methyltransferase FTSJ3 drives lung squamous cell carcinoma progression by catalyzing 2′‐O‐methylation of HSPA5 mRNA, which stabilizes BOP1 through SUMOylation and activates DRP1/SREBP1‐mediated mitochondrial fission and fatty acid oxidation. Targeting this axis with liposomal siRNA potently suppresses tumor growth and metastasis ABSTRACT Lung ...
Qin Hu +4 more
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Classification with Mixed-Type Predictors and Doubly Adaptive Group-Fused Regularisation
Classification with mixed-type predictors—continuous, categorical, and functional—is central to modern sensing and healthcare applications, yet existing estimators address this heterogeneity only partially: sparse linear methods presume a fixed ...
Sitong Zhang
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