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杨朋昆 副教授

研究方向：高维统计理论，机器学习，算法及优化。

地址： 清华大学自强科技楼4号楼（吕大龙楼）816


电话： 010-62787138


邮箱： yangpengkun@tsinghua.edu.cn


职称 副教授 地址 清华大学自强科技楼4号楼（吕大龙楼）816
电话 010-62787138 邮箱 yangpengkun@tsinghua.edu.cn
开设课程 个人主页

Background

  • 伊利诺伊大学香槟分校电子与计算机工程博士

  • 普林斯顿大学博士后

  • 清华大学统计学研究中心助理教授（2020-2024）

  • 清华大学统计与数据科学系副教授（2024-至今）

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)