:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Ma, Hanteng, Shen, Ziliang, Feng, Xingdong, Liu, Xin
Format:	Preprint
Published:	2025
Subjects:	Methodology
Online Access:	https://arxiv.org/abs/2501.02244
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Distributed High-Dimensional Quantile Regression: Estimation Efficiency and Support Recovery
by: Wang, Caixing, et al.
Published: (2024)

Transfer Learning for Kernel-based Regression
by: Wang, Chao, et al.
Published: (2023)

Community Detection on Inhomogeneous Multilayer Networks with Extreme Sparsity
by: Shen, Tao, et al.
Published: (2026)

An alternative bootstrap procedure for factor-augmented regression models
by: Jiang, Peiyun, et al.
Published: (2025)

Subgroup learning in functional regression models under the RKHS framework
by: Guan, Xin, et al.
Published: (2025)

Adaptive adequacy testing of high-dimensional factor-augmented regression model
by: Shi, Yanmei, et al.
Published: (2025)

Transfer learning for high-dimensional Factor-augmented sparse linear model
by: Fu, Bo, et al.
Published: (2025)

The Fragility of Sparsity
by: Kolesár, Michal, et al.
Published: (2023)

Modeling with Categorical Features via Exact Fusion and Sparsity Regularisation
by: Behdin, Kayhan, et al.
Published: (2026)

Eigengap Sparsity for Covariance Parsimony
by: Szwagier, Tom, et al.
Published: (2025)

Forecasting high-dimensional functional time series with dual-factor structures
by: Tang, Chen, et al.
Published: (2021)

Efficient Canonical Correlation Analysis with Sparsity
by: Wu, Zixuan, et al.
Published: (2025)

On Bayes factor functions
by: Datta, Saptati, et al.
Published: (2025)

Sparsity-Induced Global Matrix Autoregressive Model with Auxiliary Network Data
by: Wu, Sanyou, et al.
Published: (2025)

Principled Inference in Dense High-Dimensional Linear Models via Local Conditional Sparsity
by: Xiong, Wenjun, et al.
Published: (2026)

High dimensional alpha test for linear factor pricing model with $L_q$-norm
by: Zhao, Ping, et al.
Published: (2026)

High dimensional matrix estimation through elliptical factor models
by: Xu, Xinyue, et al.
Published: (2025)

The construction of augmented designs in square arrays
by: Williams, E. R., et al.
Published: (2025)

More power to you: Using machine learning to augment human coding for more efficient inference in text-based randomized trials
by: Mozer, Reagan, et al.
Published: (2023)

Graph structure learning for stable processes
by: Brück, Florian, et al.
Published: (2026)

Optimizing precision in stepped-wedge designs via machine learning and quadratic inference functions
by: Lyu, Liangbo, et al.
Published: (2026)

Learning under Latent Group Sparsity via Diffusion on Networks
by: Ghosh, Subhroshekhar, et al.
Published: (2025)

Guided structure learning of DAGs for count data
by: Nguyen, Thi Kim Hue, et al.
Published: (2022)

Unguided structure learning of DAGs for count data
by: Nguyen, Thi Kim Hue, et al.
Published: (2024)

Accounting for variable detection functions in temporal abundance modeling via transfer learning
by: Collins, Kevin M., et al.
Published: (2026)

The data augmentation algorithm
by: Roy, Vivekananda, et al.
Published: (2024)

Conic Sparsity: Estimation of Regression Parameters in Closed Convex Polyhedral Cones
by: Agarwala, Neha, et al.
Published: (2023)

Semiparametric estimation of GLMs with interval-censored covariates via an augmented Turnbull estimator
by: Toloba, Andrea, et al.
Published: (2026)

LLM Sparsity Prior for Robust Feature Selection
by: Skinner, Caleb, et al.
Published: (2026)

Sparsity meets correlation in Gaussian sequence model
by: Kotekal, Subhodh, et al.
Published: (2023)

MOSAIC: Minimax-Optimal Sparsity-Adaptive Inference for Change Points in Dynamic Networks
by: Fan, Yingying, et al.
Published: (2025)

Change-plane analysis in functional response quantile regression
by: Guan, Xin, et al.
Published: (2025)

Rectangular augmented row-column designs generated from contractions
by: Piepho, Hans-Peter, et al.
Published: (2025)

Bayesian factorization via $L_{1/2}$ shrinkage
by: Liu, Shicheng, et al.
Published: (2026)

Simultaneously accounting for winner's curse and sample structure in Mendelian randomization: bivariate rerandomized inverse variance weighted estimator
by: Liu, Xin, et al.
Published: (2026)

Incorporating external data for analyzing randomized clinical trials: A transfer learning approach
by: Gu, Yujia, et al.
Published: (2024)

Conditional cross-fitting for unbiased machine-learning-assisted covariate adjustment in randomized experiments
by: Lu, Xin, et al.
Published: (2025)

A robust score test in g-computation for covariate adjustment in randomized clinical trials leveraging different variance estimators via influence functions
by: Zhang, Xin, et al.
Published: (2025)

Targeted learning via probabilistic subpopulation matching
by: Liu, Xiaokang, et al.
Published: (2025)

Optimal design of experiments for functional linear models with dynamic factors
by: May, Caterina, et al.
Published: (2024)