Differentially Private Federated Learning: A Client Level Perspective

20 December 2017

Papers citing "Differentially Private Federated Learning: A Client Level Perspective"

50 / 230 papers shown

Title
Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Zengxia Guo Bohui An Zhongqi Lu FedML 24 0 0 15 May 2025
RiM: Record, Improve and Maintain Physical Well-being using Federated Learning Aditya Mishra Haroon R. Lone 21 0 0 09 May 2025
Efficient Full-Stack Private Federated Deep Learning with Post-Quantum Security Yiwei Zhang R. Behnia A. Yavuz Reza Ebrahimi E. Bertino FedML 45 0 0 09 May 2025
Towards One-shot Federated Learning: Advances, Challenges, and Future Directions Flora Amato Lingyu Qiu Mohammad Tanveer S. Cuomo F. Giampaolo F. Piccialli FedML 63 0 0 05 May 2025
PQS-BFL: A Post-Quantum Secure Blockchain-based Federated Learning Framework Daniel Commey Garth V. Crosby 44 0 0 03 May 2025
Differential Privacy Personalized Federated Learning Based on Dynamically Sparsified Client Updates Chuanyin Wang Yifei Zhang Neng Gao Qiang Luo FedML 71 0 0 12 Mar 2025
Controlled privacy leakage propagation throughout overlapping grouped learning Shahrzad Kiani Franziska Boenisch S. Draper FedML 77 0 0 06 Mar 2025
Heterogeneity Matters even More in Distributed Learning: Study from Generalization Perspective Masoud Kavian Romain Chor Milad Sefidgaran Abdellatif Zaidi FedML 52 1 0 03 Mar 2025
Communication-Efficient Device Scheduling for Federated Learning Using Lyapunov Optimization Jake B. Perazzone Shiqiang Wang Mingyue Ji Kevin S. Chan FedML 75 0 0 01 Mar 2025
Towards User-level Private Reinforcement Learning with Human Feedback Jingyang Zhang Mingxi Lei Meng Ding Mengdi Li Zihang Xiang Difei Xu Jinhui Xu Di Wang 47 0 0 22 Feb 2025
Noise-Aware Algorithm for Heterogeneous Differentially Private Federated Learning Saber Malekmohammadi Yaoliang Yu Yang Cao FedML 88 6 0 17 Feb 2025
Privacy-Preserving Dataset Combination Keren Fuentes Mimee Xu Irene Chen 48 0 0 09 Feb 2025
CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling Kaiyuan Zhang Siyuan Cheng Guangyu Shen Bruno Ribeiro Shengwei An Pin-Yu Chen Xinming Zhang Ninghui Li 145 1 0 28 Jan 2025
TAPFed: Threshold Secure Aggregation for Privacy-Preserving Federated Learning Runhua Xu Bo Li Chao Li J. Joshi Shuai Ma Jianxin Li FedML 43 10 0 10 Jan 2025
Differentially Private Online Federated Learning with Correlated Noise Jiaojiao Zhang Linglingzhi Zhu Mikael Johansson FedML 49 1 0 10 Jan 2025
Securing Federated Learning against Backdoor Threats with Foundation Model Integration Xiaohuan Bi Xi Li 60 1 0 23 Oct 2024
Efficient Federated Unlearning under Plausible Deniability Ayush K. Varshney V. Torra MU 40 3 0 13 Oct 2024
Breaking the Memory Wall for Heterogeneous Federated Learning via Model Splitting Chunlin Tian Li Li Kahou Tam Yebo Wu Chengzhong Xu FedML 34 3 0 12 Oct 2024
Benchmarking Data Heterogeneity Evaluation Approaches for Personalized Federated Learning Zhilong Li Xiaohu Wu Xiaoli Tang Tiantian He Yew-Soon Ong Mengmeng Chen Qiqi Liu Qicheng Lao Han Yu FedML 42 1 0 09 Oct 2024
Buffer-based Gradient Projection for Continual Federated Learning Shenghong Dai Jy-yong Sohn Yicong Chen S. Alam Ravikumar Balakrishnan Suman Banerjee N. Himayat Kangwook Lee FedML 75 2 0 03 Sep 2024
Federated Cubic Regularized Newton Learning with Sparsification-amplified Differential Privacy Wei Huo Changxin Liu Kemi Ding Karl H. Johansson Ling Shi FedML 43 0 0 08 Aug 2024
Private Collaborative Edge Inference via Over-the-Air Computation Selim F. Yilmaz Burak Hasircioglu Li Qiao Deniz Gunduz FedML 64 1 0 30 Jul 2024
Universally Harmonizing Differential Privacy Mechanisms for Federated Learning: Boosting Accuracy and Convergence Shuya Feng Meisam Mohammady Hanbin Hong Shenao Yan Ashish Kundu Binghui Wang Yuan Hong FedML 44 3 0 20 Jul 2024
Correlated Privacy Mechanisms for Differentially Private Distributed Mean Estimation Sajani Vithana V. Cadambe Flavio du Pin Calmon Haewon Jeong FedML 50 1 0 03 Jul 2024
Promoting Data and Model Privacy in Federated Learning through Quantized LoRA Jianhao Zhu Changze Lv Xiaohua Wang Muling Wu Wenhao Liu Tianlong Li Zixuan Ling Cenyuan Zhang Xiaoqing Zheng Xuanjing Huang 44 4 0 16 Jun 2024
P4: Towards private, personalized, and Peer-to-Peer learning Mohammad Maheri S. Siby Sina Abdollahi Anastasia Borovykh Hamed Haddadi 26 0 0 27 May 2024
A Systematic Review of Federated Generative Models Ashkan Vedadi Gargary Emiliano De Cristofaro AI4CE 38 2 0 26 May 2024
A Survey on Federated Analytics: Taxonomy, Enabling Techniques, Applications and Open Issues Zibo Wang Haichao Ji Yifei Zhu Dan Wang Zhu Han 51 1 0 19 Apr 2024
Generalized Policy Learning for Smart Grids: FL TRPO Approach Yunxiang Li Nicolas Mauricio Cuadrado Samuel Horváth Martin Takáč 30 0 0 27 Mar 2024
Data Reconstruction Attacks and Defenses: A Systematic Evaluation Sheng Liu Zihan Wang Yuxiao Chen Qi Lei AAML MIACV 61 4 0 13 Feb 2024
Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance Wenqi Wei Ling Liu 31 16 0 02 Feb 2024
Cross-silo Federated Learning with Record-level Personalized Differential Privacy Junxu Liu Jian Lou Li Xiong Jinfei Liu Xiaofeng Meng 48 6 0 29 Jan 2024
Personalized Federated Learning of Probabilistic Models: A PAC-Bayesian Approach Mahrokh Ghoddousi Boroujeni Andreas Krause Giancarlo Ferrari-Trecate FedML 34 3 0 16 Jan 2024
Layered Randomized Quantization for Communication-Efficient and Privacy-Preserving Distributed Learning Guangfeng Yan Tan Li Tian-Shing Lan Kui Wu Linqi Song 19 6 0 12 Dec 2023
MultiIoT: Benchmarking Machine Learning for the Internet of Things Shentong Mo Louis-Philippe Morency Russ Salakhutdinov Paul Pu Liang 30 1 0 10 Nov 2023
EcoLearn: Optimizing the Carbon Footprint of Federated Learning Talha Mehboob Noman Bashir Jesus Omana Iglesias Michael Zink David Irwin 33 0 0 27 Oct 2023
FedSym: Unleashing the Power of Entropy for Benchmarking the Algorithms for Federated Learning Ensiye Kiyamousavi Boris Kraychev Ivan Koychev FedML 16 0 0 11 Oct 2023
FedLPA: One-shot Federated Learning with Layer-Wise Posterior Aggregation Xiang Liu Liangxi Liu Feiyang Ye Yunheng Shen Xia Li Linshan Jiang Jialin Li 36 4 0 30 Sep 2023
Byzantine-Robust Federated Learning with Variance Reduction and Differential Privacy Zikai Zhang Rui Hu 41 11 0 07 Sep 2023
Mitigating Cross-client GANs-based Attack in Federated Learning Hong Huang Xinyu Lei Tao Xiang AAML 55 1 0 25 Jul 2023
Personalized Privacy Amplification via Importance Sampling Dominik Fay Sebastian Mair Jens Sjölund 68 0 0 05 Jul 2023
A First Order Meta Stackelberg Method for Robust Federated Learning Yunian Pan Tao Li Henger Li Tianyi Xu Zizhan Zheng Quanyan Zhu FedML 35 10 0 23 Jun 2023
Theoretically Principled Federated Learning for Balancing Privacy and Utility Xiaojin Zhang Wenjie Li Kai Chen Shutao Xia Qian Yang FedML 25 9 0 24 May 2023
Towards the Flatter Landscape and Better Generalization in Federated Learning under Client-level Differential Privacy Yi Shi Kang Wei Li Shen Yingqi Liu Xueqian Wang Bo Yuan Dacheng Tao FedML 41 2 0 01 May 2023
Communication and Energy Efficient Wireless Federated Learning with Intrinsic Privacy Zhenxiao Zhang Yuanxiong Guo Yuguang Fang Yanmin Gong 36 4 0 15 Apr 2023
A Game-theoretic Framework for Privacy-preserving Federated Learning Xiaojin Zhang Lixin Fan Si-Yi Wang Wenjie Li Kai Chen Qiang Yang FedML 29 4 0 11 Apr 2023
RecUP-FL: Reconciling Utility and Privacy in Federated Learning via User-configurable Privacy Defense Yue-li Cui Syed Imran Ali Meerza Zhuohang Li Luyang Liu Jiaxin Zhang Jian-Dong Liu AAML FedML 34 4 0 11 Apr 2023
Considerations on the Theory of Training Models with Differential Privacy Marten van Dijk Phuong Ha Nguyen FedML 31 2 0 08 Mar 2023
Private Read-Update-Write with Controllable Information Leakage for Storage-Efficient Federated Learning with Top $r$ Sparsification Sajani Vithana S. Ulukus FedML 30 5 0 07 Mar 2023
From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning Edwige Cyffers A. Bellet D. Basu FedML 29 5 0 24 Feb 2023