AOS

Fast Mixing of Data Augmentation Algorithms: Bayesian Probit, Logit, and Lasso Regression

Authors
Holden Lee Kexin Zhang
Research Topics
Machine Learning High-Dimensional Statistics Computational Statistics Bayesian Statistics
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Paper Information
  • Journal:
    Annals of Statistics
  • Added to Tracker:
    Apr 25, 2026
Author Details
Holden Lee
Author
Kexin Zhang
Author
Research Topics & Keywords
Machine Learning
Research Area
High-Dimensional Statistics
Research Area
Computational Statistics
Research Area
Bayesian Statistics
Research Area
Citation Information
APA Format
Holden Lee & Kexin Zhang . Fast Mixing of Data Augmentation Algorithms: Bayesian Probit, Logit, and Lasso Regression. Annals of Statistics .
BibTeX Format
@article{paper1133,
  title = { Fast Mixing of Data Augmentation Algorithms: Bayesian Probit, Logit, and Lasso Regression },
  author = { Holden Lee and Kexin Zhang },
  journal = { Annals of Statistics },
  url = { https://www.e-publications.org/ims/submission/AOS/user/submissionFile/69798?confirm=313aa3ff }
}
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