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Puning Zhao
Puning Zhao
Zhejiang Lab
Verified email at zhejianglab.com
Title
Cited by
Cited by
Year
Analysis of knn density estimation
P Zhao, L Lai
IEEE Transactions on Information Theory 68 (12), 7971-7995, 2022
322022
Minimax optimal estimation of KL divergence for continuous distributions
P Zhao, L Lai
IEEE Transactions on Information Theory 66 (12), 7787-7811, 2020
282020
Analysis of KNN information estimators for smooth distributions
P Zhao, L Lai
IEEE Transactions on Information Theory 66 (6), 3798-3826, 2019
192019
Minimax rate optimal adaptive nearest neighbor classification and regression
P Zhao, L Lai
IEEE Transactions on Information Theory 67 (5), 3155-3182, 2021
182021
Efficient classification with adaptive KNN
P Zhao, L Lai
Proceedings of the AAAI Conference on Artificial Intelligence 35 (12), 11007 …, 2021
112021
Analysis of k nearest neighbor KL divergence estimation for continuous distributions
P Zhao, L Lai
2020 IEEE International Symposium on Information Theory (ISIT), 2562-2567, 2020
62020
Minimax regression via adaptive nearest neighbor
P Zhao, L Lai
2019 IEEE International Symposium on Information Theory (ISIT), 1447-1451, 2019
52019
Robust nonparametric regression under poisoning attack
P Zhao, Z Wan
Proceedings of the AAAI Conference on Artificial Intelligence 38 (15), 17007 …, 2024
42024
Optimal stochastic nonconvex optimization with bandit feedback
P Zhao, L Lai
arXiv preprint arXiv:2103.16082, 2021
42021
A huber loss minimization approach to byzantine robust federated learning
P Zhao, F Yu, Z Wan
Proceedings of the AAAI Conference on Artificial Intelligence 38 (19), 21806 …, 2024
22024
On the convergence rates of KNN density estimation
P Zhao, L Lai
2021 IEEE International Symposium on Information Theory (ISIT), 2840-2845, 2021
22021
Nonparametric direct entropy difference estimation
P Zhao, L Lai
2018 IEEE Information Theory Workshop (ITW), 1-5, 2018
22018
CG-FedLLM: How to Compress Gradients in Federated Fune-tuning for Large Language Models
H Wu, X Li, D Zhang, X Xu, J Wu, P Zhao, Z Liu
arXiv preprint arXiv:2405.13746, 2024
12024
A Huber Loss Minimization Approach to Mean Estimation under User-level Differential Privacy
P Zhao, L Lai, L Shen, Q Li, J Wu, Z Liu
arXiv preprint arXiv:2405.13453, 2024
12024
High Dimensional Distributed Gradient Descent with Arbitrary Number of Byzantine Attackers
P Zhao, Z Wan
arXiv preprint arXiv:2307.13352, 2023
12023
Nearest neighbor methods with applications in functional estimation and machine learning
P Zhao
University of California, Davis, 2021
12021
Progressive tone mapping of brain images at single-neuron resolution
P Zhao, Z Xiong, D Liu, H Wang, C Yang, L Ding, W Ding, ZJ Zha, G Bi, ...
2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2017
12017
Learning with User-Level Local Differential Privacy
P Zhao, L Shen, R Fan, Q Li, H Wu, J Wu, Z Liu
arXiv preprint arXiv:2405.17079, 2024
2024
Enhancing Learning with Label Differential Privacy by Vector Approximation
P Zhao, R Fan, H Wu, Q Li, J Wu, Z Liu
arXiv preprint arXiv:2405.15150, 2024
2024
Emulating Full Client Participation: A Long-Term Client Selection Strategy for Federated Learning
Q Li, J Miao, P Zhao, L Zhou, S Ji, B Zhou, F Liu
arXiv preprint arXiv:2405.13584, 2024
2024
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