Puning Zhao

According to our database, Puning Zhao authored at least 33 papers between 2017 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Robust Federated Learning Under Realistic Corruption: An Iterative Filtering Approach.

Jiafei Wu, Puning Zhao, Chong Wang, Zhe Liu

IEEE Internet Things J., May, 2025

Minimax Optimal Q Learning With Nearest Neighbors.

Puning Zhao, Lifeng Lai

IEEE Trans. Inf. Theory, February, 2025

On Theoretical Limits of Learning with Label Differential Privacy.

Puning Zhao, Chuan Ma, Li Shen, Shaowei Wang, Rongfei Fan

CoRR, February, 2025

DCF-Net: Efficient Target Speaker Extraction by Leveraging Mixture and Enrollment Interactions.

Ke Xue, Rongfei Fan, Chang Sun, Puning Zhao, Jianping An

IEEE Signal Process. Lett., 2025

An Attack-Agnostic Defense Framework Against Manipulation Attacks Under Local Differential Privacy.

Puning Zhao, Zhikun Zhang, Jiawei Dong, Jiafei Wu, Zhe Liu, Shaowei Wang, Yunjun Gao

Proceedings of the IEEE Symposium on Security and Privacy, 2025

Enhancing Learning with Label Differential Privacy by Vector Approximation.

Puning Zhao, Jiafei Wu, Zhe Liu, Li Shen, Zhikun Zhang, Rongfei Fan, Le Sun, Qingming Li

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Differential Private Stochastic Optimization with Heavy-tailed Data: Towards Optimal Rates.

Puning Zhao, Jiafei Wu, Zhe Liu, Chong Wang, Rongfei Fan, Qingming Li

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

OS-Level PMC-Based Runtime Thermal Control for ARM Mobile CPUs.

Nan Che, Weihua Chen, Puning Zhao, Fei Yu, Zhijun Li, Xing Gao, Yuandi Li, Xiaogang Cui, Jie Cheng

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., July, 2024

Sequential Federated Learning in Hierarchical Architecture on Non-IID Datasets.

Xingrun Yan, Shiyuan Zuo, Rongfei Fan, Han Hu, Li Shen, Puning Zhao, Yong Luo

CoRR, 2024

Contextual Bandits for Unbounded Context Distributions.

Puning Zhao, Jiafei Wu, Zhe Liu, Huiwen Wu

CoRR, 2024

Byzantine-resilient Federated Learning Employing Normalized Gradients on Non-IID Datasets.

Shiyuan Zuo, Xingrun Yan, Rongfei Fan, Li Shen, Puning Zhao, Jie Xu, Han Hu

CoRR, 2024

Learning with User-Level Local Differential Privacy.

Puning Zhao, Li Shen, Rongfei Fan, Qingming Li, Huiwen Wu, Jiafei Wu, Zhe Liu

CoRR, 2024

Enhancing Learning with Label Differential Privacy by Vector Approximation.

Puning Zhao, Rongfei Fan, Huiwen Wu, Qingming Li, Jiafei Wu, Zhe Liu

CoRR, 2024

CG-FedLLM: How to Compress Gradients in Federated Fune-tuning for Large Language Models.

Huiwen Wu, Xiaohan Li, Deyi Zhang, Xiaogang Xu, Jiafei Wu, Puning Zhao, Zhe Liu

CoRR, 2024

Emulating Full Client Participation: A Long-Term Client Selection Strategy for Federated Learning.

Qingming Li, Juzheng Miao, Puning Zhao, Li Zhou, Shouling Ji, Bowen Zhou, Furui Liu

CoRR, 2024

Soft Label PU Learning.

Puning Zhao, Jintao Deng, Xu Cheng

CoRR, 2024

A Huber Loss Minimization Approach to Mean Estimation under User-level Differential Privacy.

Puning Zhao, Lifeng Lai, Li Shen, Qingming Li, Jiafei Wu, Zhe Liu

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Robust Federated Learning with Realistic Corruption.

Puning Zhao, Jiafei Wu, Zhe Liu

Proceedings of the Web and Big Data - 8th International Joint Conference, 2024

A Huber Loss Minimization Approach to Byzantine Robust Federated Learning.

Puning Zhao, Fei Yu, Zhiguo Wan

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Robust Nonparametric Regression under Poisoning Attack.

Puning Zhao, Zhiguo Wan

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

High Dimensional Distributed Gradient Descent with Arbitrary Number of Byzantine Attackers.

Puning Zhao, Zhiguo Wan

CoRR, 2023

Entropy Rate Estimation for Markov Chains with Continuous Distributions.

Puning Zhao, Lifeng Lai

Proceedings of the IEEE International Symposium on Information Theory, 2023

2022

Analysis of KNN Density Estimation.

Puning Zhao, Lifeng Lai

IEEE Trans. Inf. Theory, 2022

2021

Minimax Rate Optimal Adaptive Nearest Neighbor Classification and Regression.

Puning Zhao, Lifeng Lai

IEEE Trans. Inf. Theory, 2021

Optimal Stochastic Nonconvex Optimization with Bandit Feedback.

Puning Zhao, Lifeng Lai

CoRR, 2021

On the Convergence Rates of KNN Density Estimation.

Puning Zhao, Lifeng Lai

Proceedings of the IEEE International Symposium on Information Theory, 2021

Efficient Classification with Adaptive KNN.

Puning Zhao, Lifeng Lai

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Minimax Optimal Estimation of KL Divergence for Continuous Distributions.

Puning Zhao, Lifeng Lai

IEEE Trans. Inf. Theory, 2020

Analysis of KNN Information Estimators for Smooth Distributions.

Puning Zhao, Lifeng Lai

IEEE Trans. Inf. Theory, 2020

Analysis of K Nearest Neighbor KL Divergence Estimation for Continuous Distributions.

Puning Zhao, Lifeng Lai

Proceedings of the IEEE International Symposium on Information Theory, 2020

2019

Minimax Regression via Adaptive Nearest Neighbor.

Puning Zhao, Lifeng Lai

Proceedings of the IEEE International Symposium on Information Theory, 2019

2018

Nonparametric Direct Entropy Difference Estimation.

Puning Zhao, Lifeng Lai

Proceedings of the IEEE Information Theory Workshop, 2018

2017

Progressive tone mapping of brain images at single-neuron resolution.

Puning Zhao, Zhiwei Xiong, Dong Liu, Hao Wang, Chaoyu Yang, Lufeng Ding, Weiping Ding, Zheng-Jun Zha, Guoqiang Bi, Feng Wu

Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017