:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Chang, Jinyuan, Yang, Lin, Zha, Mengyue, Zhou, Wen-Xin
Format:	Preprint
Published:	2026
Subjects:	Methodology
Online Access:	https://arxiv.org/abs/2603.07505
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Near-Optimal differentially private low-rank trace regression with guaranteed private initialization
by: Zha, Mengyue
Published: (2024)

Deep neural expected shortfall regression with tail-robustness
by: Yu, Myeonghun, et al.
Published: (2025)

Edge differentially private estimation in the $β$-model via jittering and method of moments
by: Chang, Jinyuan, et al.
Published: (2021)

Robust reduced rank regression under heavy-tailed noise and missing data via non-convex penalization
by: Mai, The Tien
Published: (2025)

Optimal covariance matrix estimation for high-dimensional noise in high-frequency data
by: Chang, Jinyuan, et al.
Published: (2018)

Optimal Differentially Private PCA and Estimation for Spiked Covariance Matrices
by: Cai, T. Tony, et al.
Published: (2024)

Heavy Lasso: sparse penalized regression under heavy-tailed noise via data-augmented soft-thresholding
by: Mai, The Tien
Published: (2025)

Piece-wise linear isotonic regression
by: Kuosmanen, Timo, et al.
Published: (2026)

A simple but powerful tail index regression
by: Nicolau, João, et al.
Published: (2024)

Contrastive linear regression
by: Zhang, Boyang, et al.
Published: (2024)

Controlling the false discovery rate in high-dimensional linear models using model-X knockoffs and $p$-values
by: Chang, Jinyuan, et al.
Published: (2025)

On function-on-function linear quantile regression
by: Mutis, Muge, et al.
Published: (2025)

Transfer learning for functional linear regression via control variates
by: Yang, Yuping, et al.
Published: (2026)

Penalized function-on-function linear quantile regression
by: Beyaztas, Ufuk, et al.
Published: (2025)

Semi-parametric bulk and tail regression using spline-based neural networks
by: Majumder, Reetam, et al.
Published: (2025)

HDTSA: An R package for high-dimensional time series analysis
by: Chang, Jinyuan, et al.
Published: (2024)

Interval-censored linear quantile regression
by: Choi, Taehwa, et al.
Published: (2024)

Shrinkage linear regression for symbolic interval-valued variables
by: Rodriguez, Oldemar
Published: (2024)

A new class of composite GBII regression models with varying threshold for modelling heavy-tailed data
by: Li, Zhengxiao, et al.
Published: (2022)

Scalable Bayesian inference on high-dimensional multivariate linear regression
by: Cao, Xuan, et al.
Published: (2025)

Bayesian iterative screening in ultra-high dimensional linear regressions
by: Wang, Run, et al.
Published: (2021)

Improved LARS algorithm for adaptive LASSO in the linear regression model
by: Kayanan, Manickavasagar, et al.
Published: (2024)

Valid F-screening in linear regression
by: McGough, Olivia, et al.
Published: (2025)

Augmented balancing weights as linear regression
by: Bruns-Smith, David, et al.
Published: (2023)

Functional regression with multivariate responses
by: Luo, Ruiyan, et al.
Published: (2026)

Potential weights and implicit causal designs in linear regression
by: Chen, Jiafeng
Published: (2024)

Semi-supervised learning for linear extremile regression
by: Jiang, Rong, et al.
Published: (2025)

A flexible empirical Bayes approach to multiple linear regression and connections with penalized regression
by: Kim, Youngseok, et al.
Published: (2022)

Robust heavy-tailed versions of generalized linear models with applications in actuarial science
by: Gagnon, Philippe, et al.
Published: (2023)

Semi-supervised linear regression: enhancing efficiency and robustness in high dimensions
by: Chen, Kai, et al.
Published: (2023)

Differentially private inference framework of Riemannian manifold data
by: Jiang, Yangdi, et al.
Published: (2026)

Weighted least squares estimation by multivariate-dependent weights for linear regression models
by: Huang, Lei, et al.
Published: (2026)

Semi-parametric least-area linear-circular regression through Möbius transformation
by: Biswas, Surojit, et al.
Published: (2024)

Estimation and inference of high-dimensional partially linear regression models with latent factors
by: Shi, Yanmei, et al.
Published: (2025)

Mixtures of multivariate linear asymmetric Laplace regressions with multiple asymmetric Laplace covariates
by: Otto, Arnoldus F., et al.
Published: (2025)

Testing relevant difference in high-dimensional linear regression with applications to detect transferability
by: Liu, Xu
Published: (2025)

Statistical inference for partially shape-constrained function-on-scalar linear regression models
by: Han, Kyunghee, et al.
Published: (2024)

Sandwich regression for accurate and robust estimation in generalized linear multilevel and longitudinal models
by: Young, Elliot H., et al.
Published: (2024)

Scalable regression calibration approaches to correcting measurement error in multi-level generalized functional linear regression models with heteroscedastic measurement errors
by: Luan, Yuanyuan, et al.
Published: (2023)

Renewable estimation in linear expectile regression models with streaming data sets
by: Cao, Wei, et al.
Published: (2026)