Contact Information
605 E Springfield Ave,
Champaign, IL 61820
Biography
2022 -- present: Associate Professor, Department of Statistics, University of Illinois at Urbana-Champaign.
2018 -- 2022: Assistant Professor, Department of Statistics, University of Illinois at Urbana-Champaign.
2016 -- 2018: Assistant Professor, Department of Statistics, Florida State University.
2014 -- 2016: Postdoctoral Researcher, Department of EECS, University of California, Berkeley.
Research Interests
Bayesian inference; high-dimensional statistics; machine learning; non-parametric statistics; statistical learning theory; optimization.
Education
PhD, Statistics, Duke University, 2014.
BS, Mathematics, Tsinghua University, 2011.
Additional Campus Affiliations
Adjunct Associate Professor, Statistics
External Links
Recent Publications
Tang, R., & Yang, Y. (2024). Adaptivity of Diffusion Models to Manifold Structures. Proceedings of Machine Learning Research, 238, 1648-1656.
Zhang, Y., & Yang, Y. (2024). Bayesian model selection via mean-field variational approximation. Journal of the Royal Statistical Society. Series B: Statistical Methodology, 86(3), 742-770. https://doi.org/10.1093/jrsssb/qkad164
Zhao, W., Xu, Z., Mu, Y., Yang, Y., & Wu, W. (2024). Model-based statistical depth with applications to functional data. Journal of Nonparametric Statistics, 36(2), 313-356. https://doi.org/10.1080/10485252.2023.2226262
Zhuang, Y., Chen, X., Yang, Y., & Zhang, R. Y. (2024). STATISTICALLY OPTIMAL K-MEANS CLUSTERING VIA NONNEGATIVE LOW-RANK SEMIDEFINITE PROGRAMMING. Paper presented at 12th International Conference on Learning Representations, ICLR 2024, Hybrid, Vienna, Austria.
Chen, Y., Yao, R., Yang, Y., & Chen, J. (2023). A Gromov-Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening. Proceedings of Machine Learning Research, 202, 4804-4825.