Contact Information
725 S. Wright St.
M/C 374
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; Nonparametric statistics; Optimization.
Education
PhD, Statistics, Duke University, 2014.
BS, Mathematics, Tsinghua University, 2011.
External Links
Recent Publications
Chen, X., Lee, J. D., Li, H., & Yang, Y. (2022). Distributed Estimation for Principal Component Analysis: An Enlarged Eigenspace Analysis. Journal of the American Statistical Association, 117(540), 1775-1786. https://doi.org/10.1080/01621459.2021.1886937
Chen, Y., He, S., Yang, Y., & Liang, F. (Accepted/In press). Learning Topic Models: Identifiability and Finite-Sample Analysis. Journal of the American Statistical Association. https://doi.org/10.1080/01621459.2022.2089574
Chen, Y., Zeng, Q., Hakkani-Tur, D., Jin, D., Ji, H., & Yang, Y. (2022). Sketching as a Tool for Understanding and Accelerating Self-attention for Long Sequences. In NAACL 2022 - 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference (pp. 5187-5199). (NAACL 2022 - 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference). Association for Computational Linguistics (ACL).
Liu, M., Shang, Z., Yang, Y., & Cheng, G. (2022). Nonparametric Testing Under Randomized Sketching. IEEE transactions on pattern analysis and machine intelligence, 44(8), 4280-4290. https://doi.org/10.1109/TPAMI.2021.3063223
Tang, R., & Yang, Y. (2022). Bayesian inference for risk minimization via exponentially tilted empirical likelihood. Journal of the Royal Statistical Society. Series B: Statistical Methodology, 84(4), 1257-1286. https://doi.org/10.1111/rssb.12510
