Cover Image

Robust and Sparse Generalized Linear Models for High-Dimensional Data via Maximum Mean Discrepancy

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kang, Xiaoning, Kang, Lulu
Format:	Preprint
Published:	2026
Subjects:	Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Generative Approach to Joint Modeling of Quantitative and Qualitative Responses
by: Kang, Xiaoning, et al.
Published: (2021)

Bayesian Auxiliary Variable Model for Birth Records Data with Qualitative and Quantitative Responses
by: Kang, Xiaoning, et al.
Published: (2020)

Kernel Discrepancy-Based Rerandomization for Controlled Experiments
by: Li, Yiou, et al.
Published: (2019)

Convolutional Maximum Mean Discrepancy for Inference in Noisy Data
by: Vashistha, Ritwik, et al.
Published: (2026)

Robust Joint Modeling for Data with Continuous and Binary Responses
by: Wang, Yu, et al.
Published: (2026)

Estimation of time series by Maximum Mean Discrepancy
by: Alquier, Pierre, et al.
Published: (2026)

Optimal Kernel Learning for Gaussian Process Models with High-Dimensional Input
by: Kang, Lulu, et al.
Published: (2025)

Maximum Mean Discrepancy with Unequal Sample Sizes via Generalized U-Statistics
by: Wei, Aaron, et al.
Published: (2025)

Goodness-of-Fit Tests for Censored and Truncated Data: Maximum Mean Discrepancy Over Regular Functionals
by: Escanciano, Juan Carlos, et al.
Published: (2026)

Spatial Sign based Direct Sparse Linear Discriminant Analysis for High Dimensional Data
by: Zhuang, Dan, et al.
Published: (2025)

Data-Driven Random Projection and Screening for High-Dimensional Generalized Linear Models
by: Parzer, Roman, et al.
Published: (2024)

Collaborative Inference for Sparse High-Dimensional Models with Non-Shared Data
by: Gu, Yifan, et al.
Published: (2025)

Nonparametric Shrinkage Estimation in High Dimensional Generalized Linear Models via Polya Trees
by: Weinstein, Asaf, et al.
Published: (2019)

High Dimensional Gaussian and Bootstrap Approximations in Generalized Linear Models
by: Choudhury, Mayukh, et al.
Published: (2026)

A Bayesian Non-parametric Approach to Generative Models: Integrating Variational Autoencoder and Generative Adversarial Networks using Wasserstein and Maximum Mean Discrepancy
by: Fazeli-Asl, Forough, et al.
Published: (2023)

Spectral Deconfounding for High-Dimensional Sparse Additive Models
by: Scheidegger, Cyrill, et al.
Published: (2023)

Gaussian Process Assisted Active Learning of Physical Laws
by: Chen, Jiuhai, et al.
Published: (2019)

Collaborative Analysis for Paired A/B Testing Experiments
by: Zhang, Qiong, et al.
Published: (2024)

A Maximin $Φ_{p}$-Efficient Design for Multivariate GLM
by: Li, Yiou, et al.
Published: (2020)

Bayesian Bridge Gaussian Process Regression
by: Xu, Minshen, et al.
Published: (2025)

Covariate Balancing Based on Kernel Density Estimates for Controlled Experiments
by: Li, Yiou, et al.
Published: (2020)

Statistical Inference for High-Dimensional Robust Linear Regression Models via Recursive Online-Score Estimation
by: Zheng, Dian, et al.
Published: (2025)

glmmPen: High Dimensional Penalized Generalized Linear Mixed Models
by: Heiling, Hillary M., et al.
Published: (2023)

Weighted Average Ensemble for Cholesky-based Covariance Matrix Estimation
by: Kang, Xiaoning, et al.
Published: (2025)

Sparse Variable Selection on High Dimensional Heterogeneous Data with Tree Structured Responses
by: Liu, Hui, et al.
Published: (2017)

Sparse Data-Driven Random Projection in Regression for High-Dimensional Data
by: Parzer, Roman, et al.
Published: (2023)

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

High-Dimensional Independence Testing via Maximum and Average Distance Correlations
by: Shen, Cencheng, et al.
Published: (2020)

SLOPE and Designing Robust Studies for Generalization
by: Miao, Xinran, et al.
Published: (2025)

Exact Posterior Mean and Covariance for Generalized Linear Mixed Models
by: Zhang, Tonglin
Published: (2024)

Design of Experiments for Emulations: A Selective Review from a Modeling Perspective
by: Deng, Xinwei, et al.
Published: (2025)

A Deterministic Sampling Method via Maximum Mean Discrepancy Flow with Adaptive Kernel
by: Chen, Yindong, et al.
Published: (2021)

Adaptive Multi-Prior Lasso for High-Dimensional Generalized Linear Models
by: Xu, Fuzhi, et al.
Published: (2026)

Fast and Scalable Cellwise-Robust Ensembles for High-Dimensional Data
by: Christidis, Anthony, et al.
Published: (2026)

Bayesian Variable Selection and Sparse Estimation for High-Dimensional Graphical Models
by: Chakravarti, Anwesha, et al.
Published: (2024)

Model Form Identification in High-Dimensional Functional Linear Regressions
by: Guo, Xingche, et al.
Published: (2026)

Robust Penalized Estimators for High--Dimensional Generalized Linear Models
by: Valdora, Marina, et al.
Published: (2023)

Univariate-Guided Sparse Regression for Biobank-Scale High-Dimensional Omics Data
by: Richland, Joshua, et al.
Published: (2025)

Locally Optimal Design for A/B Testing in the Presence of Covariates and Network Connection
by: Zhang, Qiong, et al.
Published: (2020)

Forward Regression via Gram-Schmidt Orthogonalization for Ultra-High Dimensional Linear Models
by: Chen, Jialuo, et al.
Published: (2025)