Polynomial methods in statistical inference: theory and practice, Yihong Wu, Pengkun Yang, Foundations and Trends® in Communications and Information Theory, now publisher, 2020.
On the best approximation by finite Gaussian mixtures, Yun Ma, Yihong Wu, Pengkun Yang, IEEE Transactions on Information Theory, 2025.
Global Convergence of Federated Learning for Mixed Regression, Lili Su, Jiaming Xu, Pengkun Yang, IEEE Transactions on Information Theory, 2024.
Sampling for Remote Estimation of an Ornstein-Uhlenbeck Process through Channel with Unknown Delay Statistics, Yuchao Chen, Jiantao Wang, Haoyue Tang, Pengkun Yang, Leandros Tassiulas, Journal of Communications and Networks, 2023.
Semi-supervised Transfer Learning with Hierarchical Self-regularization, Xingjian Li, Abulikemu Abuduweili, Humphrey Shi, Pengkun Yang, Haoyi Xiong, Chengzhong Xu, and Dejing Dou, Pattern Recognition, 2023.
A Non-parametric View of FedAvg and FedProx: Beyond Stationary Points, Lili Su, Jiaming Xu, Pengkun Yang, Journal of Machine Learning Research, 2023.
Age Optimal Sampling Under Unknown Delay Statistics, Haoyue Tang, Yuchao Chen, Jintao Wang, Pengkun Yang, Leandros Tassiulas, IEEE Transactions on Information Theory, 2023.
Optimal estimation of high-dimensional location Gaussian mixtures, Natalie Doss, Yihong Wu, Pengkun Yang, Harrison H. Zhou, Annals of Statistics, 2023.
Utilization of text mining as a big data analysis tool for food science and nutrition, Dandan Tao, Pengkun Yang, Hao Feng, Comprehensive Reviews In Food Science And Food Safety, 2020.
Optimal estimation of Gaussian mixtures via denoised method of moments. Yihong Wu, Pengkun Yang, Annals of Statistics, 2020. [code]
Chebyshev polynomials, moment matching, and optimal estimation of the unseen, Yihong Wu, Pengkun Yang, Annals of Statistics, 2019. [code]
Sample complexity of the distinct elements problem, Yihong Wu, Pengkun Yang, Mathematical Statistics and Learning, 2018.
Minimax Rates of Entropy Estimation on Large Alphabets via Best Polynomial Approximation, Yihong Wu, Pengkun Yang, IEEE Transactions on Information Theory, 2016. [code]
Identifiability and Estimation in High-Dimenisonal Nonparametric Latent Structure Models, Yichen Lyu, Pengkun Yang, COLT 2025.
Fast and Multiphase Rates for Nearest Neighbor Classifiers, Pengkun Yang, Jingzhao Zhang, COLT 2025.
Sample Complexity of Correlation Detection in the Gaussian Wigner Model, Dong Huang, Pengkun Yang, ICML 2025.
Information-Theoretic Thresholds for the Alignments of Partially Correlated Graphs, Dong Huang, Xianwen Song, Pengkun Yang, COLT 2024.
Deep Active Learning with Noise Stability, Xingjian Li, Pengkun Yang, Tianyang Wang, Xueying Zhan, Min Xu, Dejing Dou, Chengzhong Xu, AAAI 2024.
Modeling of Multi-Level Spin-Orbit Torque-MRAM: Scalability, Stochasticity, and Variations, Zihan Tong, Shun Kong Cheung, Zheyu Ren, Pengkun Yang, Qiming Shao, IEEE International Magnetic Conference, 2023.
On the best approximation by finite Gaussian mixtures, Yun Ma, Yihong Wu, Pengkun Yang, ISIT 2023.
Global Convergence of Federated Learning for Mixed Regression, Lili Su, Jiaming Xu, Pengkun Yang, NeurIPS 2022.
Boosting active learning via improving test performance, Tianyang Wang, Xingjian Li, Pengkun Yang, Guosheng Hu, Xiangrui Zeng, Siyu Huang, Cheng-Zhong Xu, Min Xu, AAAI 2022.
Modeling from Features: a Mean-field Framework for Over-parameterized Deep Neural Networks, Cong Fang, Jason D. Lee, Pengkun Yang, Tong Zhang, COLT 2021.
On Learning Over-parameterized Neural Networks: A Functional Approximation Perspective, Lili Su, Pengkun Yang, NeurIPS 2019.
Optimal entropy estimation on large alphabets via best polynomial approximation, Yihong Wu, Pengkun Yang, ISIT 2015.
Best Student Paper Award
Software defined radio implementation of signaling splitting in hyper-cellular network, Tao Zhao, Pengkun Yang, Huimin Pan, Ruichen Deng, Sheng Zhou, Zhisheng Niu, SIRF workshop of SIGCOMM 2013.
Per-packet load-balanced, low-latency routing for clos-based data center networks, Jiaxin Cao, Rui Xia, Pengkun Yang, Chuanxiong Guo, Guohan Lu, Lihua Yuan, Yixin Zheng, Haitao Wu, Yongqiang Xiong, Dave Maltz, CoNEXT 2013.
Collaborative Learning with Shared Linear Representations: Statistical Rates and Optimal Algorithms, Xiaochun Niu, Lili Su, Jiaming Xu, Pengkun Yang.
On the Convergence Rates of Federated Q-Learning across Heterogeneous Environments, Muxing Wang, Pengkun Yang, Lili Su.
Minimax estimation of functionals in sparse vector model with correlated observations, Yuhao Wang, Pengkun Yang, Alexandre B Tsybakov.
Federated learning in the presence of adversarial client unavailability, Lili Su, Ming Xiang, Jiaming Xu, Pengkun Yang.