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Pengkun Yang Associate Professor

Research Areas:theory and algorithms for high-dimensional statistics, mathematical data science, statistical machine learning, optimization

Office: Room 816, Lyu Dalong Building, Tsinghua University


Phone: +86-10-62787138


Email: yangpengkun@tsinghua.edu.cn


职称 Associate Professor 地址 Room 816, Lyu Dalong Building, Tsinghua University
电话 +86-10-62787138 邮箱 yangpengkun@tsinghua.edu.cn
个人主页

Work Experiences:

Education:

Monographs:

Journal publications:

  • L. Su, M. Xiang, J. Xu, P. Yang (α-β)“Federated Learning under Adversarial Silence Attacks,”INFORMS Journal on Computing, 2026.

  • D. Huang, X. Song, P. Yang (α-β)“Information-Theoretic Thresholds for the Alignments of Partially Correlated Graphs,”IEEE Transactions on Information Theory, 2025.

  • M. Wang, P. Yang, L. Su“On the Convergence Rates of Federated Q-Learning across Heterogeneous Environments,”Transactions on Machine Learning Research, 2025.

  • Y. Ma, Y. Wu, P. Yang, (α-β)“On the Best Approximation by Finite Gaussian Mixtures,”IEEE Transactions on Information Theory, 2025.

  • L. Su, J. Xu, P. Yang, (α-β)“Global Convergence of Federated Learning for Mixed Regression,”IEEE Transactions on Information Theory, 2024.

  • Y. Chen, J. Wang, H. Tang, P. Yang, L. Tassiulas,“Sampling for Remote Estimation of an Ornstein-Uhlenbeck Process through Channel with Unknown Delay Statistics,”Journal of Communications and Networks, 2023.

  • X. Li, A. Abuduweili, H. Shi, P. Yang, H. Xiong, C. Xu, D. Dou,“Semi-supervised Transfer Learning with Hierarchical Self-regularization,”Pattern Recognition, Volume 144, 109831, 2023.

  • L. Su, J. Xu, P. Yang, (α-β)“A Non-parametric View of FedAvg and FedProx: Beyond Stationary Points,”Journal of Machine Learning Research, Volume 24, Issue 203, pp. 1-48, 2023.

  • H. Tang, Y. Chen, J. Wang, P. Yang, L. Tassiulas,“Age Optimal Sampling Under Unknown Delay Statistics,”IEEE Transactions on Information Theory, Volume 69, Issue 2, pp. 1295-1314, 2023.

  • N. Doss, Y. Wu, P. Yang, and H. H. Zhou, (α-β)“Optimal estimation of high-dimensional Gaussian location mixtures,”Annals of Statistics, Volume 51, Issue 1, pp. 62-95, 2023.Selected paper by the Annals of Statistics editorial board

  • Y. Wu, P. Yang, (α-β)“Optimal estimation of Gaussian mixtures via denoised method of moments,”Annals of Statistics, Volume 48, Number 4, pp. 1981-2007, 2020.

  • D. Tao, P. Yang, H. Feng,“Utilization of text mining as a big data analysis tool for food science and nutrition,”Comprehensive Reviews in Food Science and Food Safety, Volume 19, Number 2, pp. 875-894,2020.

  • Y. Wu, P. Yang, (α-β)“Chebyshev polynomials, moment matching, and optimal estimation of the unseen,”Annals of Statistics, Volume 47, Number 2, pp. 857-883, 2019.

  • Y. Wu, P. Yang, (α-β)“Sample complexity of the distinct elements problem,”Mathematical Statistics and Learning, Volume 1, Issue 1, pp. 37-72, 2018.

  • Y. Wu, P. Yang, (α-β)“Minimax rates of entropy estimation on large alphabets via best polynomial approximation,”IEEE Transactions on Information Theory, Volume 62, Issue 6, pp. 3702–3720, 2016.

Conference publications: 

  • D. Huang, C. Tian, P. Yang, (α-β)“Attributed Network Alignment: Statistical Limits and Efficient Algorithm,”International Conference on Machine Learning (ICML), 2026.

  • J. Sun, P. Yang, (α-β)“Hallucination Detection from Structural Reasoning Model,”International Conference on Machine Learning (ICML), 2026.

  • Y. Lyu, P. Yang, (α-β)“Identifiability and Estimation in High-Dimenisonal Nonparametric Latent Structure Models,”Conference on Learning Theory (COLT), 2025.

  • P. Yang, J. Zhang, (α-β)“Fast and Multiphase Rates for Nearest Neighbor Classifiers,”Conference on Learning Theory (COLT), 2025.

  • D. Huang, P. Yang (α-β) “Sample Complexity of Correlation Detection in the Gaussian Wigner Model,” International Conference on Machine Learning (ICML), 2025.

  • D. Huang, X. Song, P. Yang (α-β)“Information-Theoretic Thresholds for the Alignments of Partially Correlated Graphs,”Conference on Learning Theory (COLT), 2024.

  • X. Li, P. Yang, T. Wang, X. Zhan, M. Xu, D. Dou, C. Xu,“Deep active learning with noise stability,”AAAI Conference on Artificial Intelligence (AAAI), 2024.

  • Z. Tong, S. Cheung, Z. Ren, P. Yang, Q. Shao,“Modeling of Multi-Level Spin-Orbit Torque-MRAM: Scalability, Stochasticity, and Variations,”IEEE International Magnetic Conference, 2023.

  • Y. Ma, Y. Wu, P. Yang, (α-β)“On the best approximation by finite Gaussian mixtures,”IEEE International Symposium on Information Theory (ISIT), 2023.

  • L. Su, J. Xu, P. Yang, (α-β)“Global Convergence of Federated Learning for Mixed Regression,”Advances in Neural Information Processing Systems (NeurIPS), 2022.

  • T. Wang, X. Li, P. Yang, G. Hu, X. Zeng, S. Huang, C. Xu, M. Xu,“Boosting active learning via improving test performance,”AAAI Conference on Artificial Intelligence (AAAI), 2022.

  • C. Fang, J. Lee, P. Yang, T. Zhang, (α-β)“Modeling from Features: a Mean-field Framework for Over-parameterized Deep Neural Networks,”Conference on Learning Theory (COLT), 2021.

  • L. Su, P. Yang, (α-β)“On learning over-parameterized neural networks: a functional approximation perspective,”Advances in Neural Information Processing Systems (NeurIPS), 2019.

  • Y. Wu, P. Yang, (α-β)“Optimal entropy estimation on large alphabets via best polynomial approximation,”IEEE International Symposium on Information Theory (ISIT), 2015.Jack Keil Wolf ISIT Student Paper Award

  • T. Zhao, P. Yang, H. Pan, R. Deng, S. Zhou, Z. Niu,“Software defined radio implementation of signaling splitting in hyper-cellular network,”ACM SIGCOMM Second workshop on Software radio implementation forum (SRIF), 2013.

  • J. Cao, R. Xia, P. Yang, C. Guo, G. Lu, L. Yuan, Y. Zheng, H. Wu, Y. Xiong, D. Maltz,“Per-packet load-balanced, low-latency routing for clos-based data center networks,”ACM Conference on Emerging Networking Experiments and Technologies (CoNEXT), 2013

Awards:

  • Thomas M. Cover Dissertation Award, 2020 IEEE Information Theory Society

  • Shun Lien Chuang Memorial Award for Excellence in Graduate Education, 2018 University of Illinois at Urbana-Champaign

  • Jack Keil Wolf ISIT Student Paper Award, 2015 IEEE International Symposium on Information Theory (ISIT)

  • Star of Tomorrow Internship Award of Excellence, 2013 Microsoft Research Asia (MSRA)   

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