A Unified Approach for Computing Wasserstein Barycenters of Discrete and Continuous Measures
Peng Xu, Changbo Zhu, Xiaohui Chen. A Unified Approach for Computing Wasserstein Barycenters of Discrete and Continuous Measures. arXiv: 2605.11270.
CV
Education
- PhD in Statistics, University of Illinois at Urbana-Champaign, Since 2020
- M.A. in Statistics, Columbia University, 2018
- M.S. in Financial Engineering, University of Illinois at Urbana-Champaign, 2016
- B.S. in Mathematics and Statistics, University of Illinois at Urbana-Champaign, 2015
- B.S. in Finance, University of Illinois at Urbana-Champaign, 2015
Awards and Honors
- 2023 Doctoral Student Teaching Award
Work Experiences
- Visiting Student. Department of Mathematics, University of Southern California. 2024.
- Advised by Prof. Xiaohui Chen and Prof. Quntao Zhuang.
- Research Associate. Department of Statistics, Columbia University. 2019.
- Advised by Prof. Bodhisattva Sen and Dr. Margaret Holen on seperate projects.
Publications
Scalable Second-order Riemannian Optimization for \(K\)-means Clustering
Peng Xu, Chun Ying Hou, Xiaohui Chen, Richard Y. Zhang. Scalable Second-order Riemannian Optimization for K-means Clustering. *The Fourteenth International Conference on Learning Representations* (ICLR 2026). arXiv:2509.21675.
Holographic Deep Thermalization for Secure and Efficient Quantum Random State Generation
Bingzhi Zhang, Peng Xu, Xiaohui Chen, Quntao Zhuang. (2025). Holographic Deep Thermalization for Secure and Efficient Quantum Random State Generation. doi: 10.1038/s41467-025-61546-y.
Embedding Empirical Distributions for Computing Optimal Transport Maps
Mingchen Jiang, Peng Xu, Xichen Ye, Xiaohui Chen, Yun Yang, Yifan Chen. (2025). Embedding Empirical Distributions for Computing Optimal Transport Maps. 2025 IEEE International Symposium on Information Theory.
Generative Quantum Machine Learning via Denoising Diffusion Probabilistic Models
Bingzhi Zhang, Peng Xu, Xiaohui Chen, Quntao Zhuang. (2024). Generative Quantum Machine Learning via Denoising Diffusion Probabilistic Models. Phys. Rev. Lett., 132, 100602. doi: 10.1103/PhysRevLett.132.100602
Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions
Wenda Zhou, Shuaiwen Wang, Peng Xu, Haiho Lu, Arian Maleki, Vahab Mirrokni. (2019). Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions. 2019 INFORMS Workshop on Data Mining and Decision Analytics.
orthoDr: Semiparametric Dimension Reduction via Orthogonality Constrained Optimization
Ruoqing Zhu, Jiyang Zhang, Ruilin Zhao, Peng Xu, Wenzhuo Zhou, Xin Zhang. (2019). orthoDr: Semiparametric Dimension Reduction via Orthogonality Constrained Optimization. The R Journal, 11(2), 24–37.
Talks
Scalable Second-order Riemannian Optimization for \(K\)-means Clustering
Poster at the Fourteenth International Conference on Learning Representations, Rio de Janeiro, Brazil
Generative quantum machine learning via denoising diffusion probabilistic models
Talk at 2024 APS March Meeting, Minneapolis, MN