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2020 – today
- 2025
[j6]Puning Zhao
, Lifeng Lai:
Minimax Optimal Q Learning With Nearest Neighbors. IEEE Trans. Inf. Theory 71(2): 1300-1322 (2025)- [c13]Puning Zhao, Jiafei Wu, Zhe Liu, Chong Wang, Rongfei Fan, Qingming Li:
Differential Private Stochastic Optimization with Heavy-tailed Data: Towards Optimal Rates. AAAI 2025: 22795-22803 - [i20]Puning Zhao, Chuan Ma, Li Shen, Shaowei Wang, Rongfei Fan:
On Theoretical Limits of Learning with Label Differential Privacy. CoRR abs/2502.14309 (2025) - 2024
- [j5]Nan Che, Weihua Chen, Puning Zhao, Fei Yu, Zhijun Li, Xing Gao, Yuandi Li, Xiaogang Cui, Jie Cheng:
OS-Level PMC-Based Runtime Thermal Control for ARM Mobile CPUs. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 43(7): 2023-2036 (2024) - [c12]Puning Zhao, Zhiguo Wan:
Robust Nonparametric Regression under Poisoning Attack. AAAI 2024: 17007-17015 - [c11]Puning Zhao, Fei Yu, Zhiguo Wan:
A Huber Loss Minimization Approach to Byzantine Robust Federated Learning. AAAI 2024: 21806-21814 - [c10]Puning Zhao, Jiafei Wu, Zhe Liu:
Robust Federated Learning with Realistic Corruption. APWeb/WAIM (4) 2024: 228-242 - [c9]Puning Zhao, Lifeng Lai, Li Shen, Qingming Li, Jiafei Wu, Zhe Liu:
A Huber Loss Minimization Approach to Mean Estimation under User-level Differential Privacy. NeurIPS 2024 - [i19]Puning Zhao, Jintao Deng, Xu Cheng:
Soft Label PU Learning. CoRR abs/2405.01990 (2024) - [i18]Puning Zhao, Lifeng Lai, Li Shen, Qingming Li, Jiafei Wu, Zhe Liu:
A Huber Loss Minimization Approach to Mean Estimation under User-level Differential Privacy. CoRR abs/2405.13453 (2024) - [i17]Qingming Li, Juzheng Miao, Puning Zhao, Li Zhou, Shouling Ji, Bowen Zhou, Furui Liu:
Emulating Full Client Participation: A Long-Term Client Selection Strategy for Federated Learning. CoRR abs/2405.13584 (2024) - [i16]Huiwen Wu, Xiaohan Li, Deyi Zhang, Xiaogang Xu, Jiafei Wu, Puning Zhao, Zhe Liu:
CG-FedLLM: How to Compress Gradients in Federated Fune-tuning for Large Language Models. CoRR abs/2405.13746 (2024) - [i15]Puning Zhao, Rongfei Fan, Huiwen Wu, Qingming Li, Jiafei Wu, Zhe Liu:
Enhancing Learning with Label Differential Privacy by Vector Approximation. CoRR abs/2405.15150 (2024) - [i14]Puning Zhao, Li Shen, Rongfei Fan, Qingming Li, Huiwen Wu, Jiafei Wu, Zhe Liu:
Learning with User-Level Local Differential Privacy. CoRR abs/2405.17079 (2024) - [i13]Shiyuan Zuo, Xingrun Yan, Rongfei Fan, Li Shen, Puning Zhao, Jie Xu, Han Hu:
Byzantine-resilient Federated Learning Employing Normalized Gradients on Non-IID Datasets. CoRR abs/2408.09539 (2024) - [i12]Puning Zhao, Jiafei Wu, Zhe Liu, Huiwen Wu:
Contextual Bandits for Unbounded Context Distributions. CoRR abs/2408.09655 (2024) - [i11]Xingrun Yan, Shiyuan Zuo, Rongfei Fan, Han Hu, Li Shen, Puning Zhao, Yong Luo:
Sequential Federated Learning in Hierarchical Architecture on Non-IID Datasets. CoRR abs/2408.09762 (2024) - [i10]Puning Zhao, Jiafei Wu, Zhe Liu, Chong Wang, Rongfei Fan, Qingming Li:
Differential Private Stochastic Optimization with Heavy-tailed Data: Towards Optimal Rates. CoRR abs/2408.09891 (2024) - 2023
- [c8]Puning Zhao, Lifeng Lai:
Entropy Rate Estimation for Markov Chains with Continuous Distributions. ISIT 2023: 1884-1889 - [i9]Puning Zhao, Zhiguo Wan:
Robust Nonparametric Regression under Poisoning Attack. CoRR abs/2305.16771 (2023) - [i8]Puning Zhao, Zhiguo Wan:
High Dimensional Distributed Gradient Descent with Arbitrary Number of Byzantine Attackers. CoRR abs/2307.13352 (2023) - [i7]Puning Zhao, Lifeng Lai:
Minimax Optimal Q Learning with Nearest Neighbors. CoRR abs/2308.01490 (2023) - [i6]Puning Zhao, Fei Yu, Zhiguo Wan:
A Huber Loss Minimization Approach to Byzantine Robust Federated Learning. CoRR abs/2308.12581 (2023) - 2022
- [j4]Puning Zhao, Lifeng Lai:
Analysis of KNN Density Estimation. IEEE Trans. Inf. Theory 68(12): 7971-7995 (2022) - 2021
- [j3]Puning Zhao, Lifeng Lai:
Minimax Rate Optimal Adaptive Nearest Neighbor Classification and Regression. IEEE Trans. Inf. Theory 67(5): 3155-3182 (2021) - [c7]Puning Zhao, Lifeng Lai:
Efficient Classification with Adaptive KNN. AAAI 2021: 11007-11014 - [c6]Puning Zhao, Lifeng Lai:
On the Convergence Rates of KNN Density Estimation. ISIT 2021: 2840-2845 - [i5]Puning Zhao, Lifeng Lai:
Optimal Stochastic Nonconvex Optimization with Bandit Feedback. CoRR abs/2103.16082 (2021) - 2020
- [j2]Puning Zhao, Lifeng Lai:
Analysis of KNN Information Estimators for Smooth Distributions. IEEE Trans. Inf. Theory 66(6): 3798-3826 (2020) - [j1]Puning Zhao, Lifeng Lai:
Minimax Optimal Estimation of KL Divergence for Continuous Distributions. IEEE Trans. Inf. Theory 66(12): 7787-7811 (2020) - [c5]Puning Zhao, Lifeng Lai:
Analysis of K Nearest Neighbor KL Divergence Estimation for Continuous Distributions. ISIT 2020: 2562-2567 - [i4]Puning Zhao, Lifeng Lai:
Minimax Optimal Estimation of KL Divergence for Continuous Distributions. CoRR abs/2002.11599 (2020) - [i3]Puning Zhao, Lifeng Lai:
Analysis of KNN Density Estimation. CoRR abs/2010.00438 (2020)
2010 – 2019
- 2019
- [c4]Puning Zhao, Lifeng Lai:
Minimax Regression via Adaptive Nearest Neighbor. ISIT 2019: 1447-1451 - [i2]Puning Zhao, Lifeng Lai:
Minimax Rate Optimal Adaptive Nearest Neighbor Classification and Regression. CoRR abs/1910.10513 (2019) - 2018
- [c3]Puning Zhao, Lifeng Lai:
Analysis of KNN Information Estimators for Smooth Distributions. Allerton 2018: 322-327 - [c2]Puning Zhao, Lifeng Lai:
Nonparametric Direct Entropy Difference Estimation. ITW 2018: 1-5 - [i1]Puning Zhao, Lifeng Lai:
Analysis of KNN Information Estimators for Smooth Distributions. CoRR abs/1810.11571 (2018) - 2017
- [c1]Puning Zhao, Zhiwei Xiong, Dong Liu, Hao Wang, Chaoyu Yang, Lufeng Ding, Weiping Ding, Zheng-Jun Zha, Guoqiang Bi, Feng Wu:
Progressive tone mapping of brain images at single-neuron resolution. GlobalSIP 2017: 958-961
Coauthor Index
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