About me

Welcome to my homepage!

I am a third-year PhD student in the Department of Statistics & Data Science at Yale University. I am very fortunate to be advised by Prof. Zhou Fan and Prof. Andre Wibisono. My current research interests lie in the intersection of theoretical statistics and machine learning theory, with a recent focus on statistical physics and sampling algorithms.

Prior to Yale, I got my BS in Statistics and BPhil in Logic from Sun Yet-Sen University (SYSU) in Guangzhou China. During my junior and senior years, I worked on machine learning applications in genetics with Prof. Liming Liang at Harvard Biostatistics and Prof. Yun Li at University of North Carolina, Chapel Hill (UNC-CH) Biostatistics.

Email: yingxi.yang@yale.edu

Recent Publications and Preprints

*: alphabetical

• Asymptotic mutual information in quadratic estimation problems over compact groups
  Kaylee Y. Yang, Timothy L. H. Wee, Zhou Fan

• Optimal score estimation via empirical Bayes smoothing
  Andre Wibisono, Yihong Wu, Kaylee Y. Yang*

• Convergence of the inexact Langevin algorithm and score-based generative models in KL divergence
  Kaylee Y. Yang, Andre Wibisono

• Convergence in KL and Rényi divergence of the unadjusted Langevin algorithm using estimated score [Poster] (preliminary version of the preprint above)
  Kaylee Y. Yang, Andre Wibisono
  NeurIPS 2022 Workshop on Score-Based Methods

See my Google Scholar for a complete publication list.

Teaching Experience

• TA, S&DS 242/542 Theory of Statistics, 2024 Spring
  • Instructor: Dr. Robert Wooster
• TA, S&DS 265/565 Introductory Machine Learning, 2023 Fall
  • Instructor: Dr. John Lafferty
• TA, S&DS 364/664 Information Theory, 2023 Spring
  • Instructor: Dr. Andrew Barron
• TA, S&DS 431/631 Optimization and Computation, 2022 Fall
  • Instructor: Dr. Zhuoran Yang

Last updated: April 18, 2024