Differentially Private Meta-Learning

12 September 2019

Papers citing "Differentially Private Meta-Learning"

48 / 48 papers shown

Title
Dyn-D $^2$ P: Dynamic Differentially Private Decentralized Learning with Provable Utility Guarantee Zehan Zhu Yan Huang Xin Wang Shouling Ji Jinming Xu 26 0 0 10 May 2025
Adaptive Clipping for Privacy-Preserving Few-Shot Learning: Enhancing Generalization with Limited Data Kanishka Ranaweera Dinh C. Nguyen P. Pathirana David B. Smith Ming Ding Thierry Rakotoarivelo A. Seneviratne 31 0 0 27 Mar 2025
Fine-Tuning Large Language Models with User-Level Differential Privacy Zachary Charles Arun Ganesh Ryan McKenna H. B. McMahan Nicole Mitchell Krishna Pillutla Keith Rush 36 11 0 10 Jul 2024
Noise-Aware Differentially Private Regression via Meta-Learning Ossi Raisa Stratis Markou Matthew Ashman W. Bruinsma Marlon Tobaben Antti Honkela Richard Turner 71 1 0 12 Jun 2024
Privacy Challenges in Meta-Learning: An Investigation on Model-Agnostic Meta-Learning Mina Rafiei Mohammadmahdi Maheri Hamid R. Rabiee 32 0 0 01 Jun 2024
Advancing Explainable AI Toward Human-Like Intelligence: Forging the Path to Artificial Brain Yongchen Zhou Richard Jiang 24 2 0 07 Feb 2024
DP-BREM: Differentially-Private and Byzantine-Robust Federated Learning with Client Momentum Xiaolan Gu Ming Li Lishuang Xiong FedML 30 4 0 22 Jun 2023
Mobilizing Personalized Federated Learning in Infrastructure-Less and Heterogeneous Environments via Random Walk Stochastic ADMM Ziba Parsons Fei Dou Houyi Du Zheng Song Jin Lu 32 3 0 25 Apr 2023
Multi-Task Differential Privacy Under Distribution Skew Walid Krichene Prateek Jain Shuang Song Mukund Sundararajan Abhradeep Thakurta Li Zhang FedML 38 3 0 15 Feb 2023
Mnemosyne: Learning to Train Transformers with Transformers Deepali Jain K. Choromanski Kumar Avinava Dubey Sumeet Singh Vikas Sindhwani Tingnan Zhang Jie Tan OffRL 36 9 0 02 Feb 2023
Privacy-preserving Decentralized Deep Learning with Multiparty Homomorphic Encryption Guowen Xu Guanlin Li Shangwei Guo Tianwei Zhang Hongwei Li FedML 28 3 0 11 Jul 2022
A Generative Framework for Personalized Learning and Estimation: Theory, Algorithms, and Privacy Kaan Ozkara Antonious M. Girgis Deepesh Data Suhas Diggavi FedML 16 3 0 05 Jul 2022
On Privacy and Personalization in Cross-Silo Federated Learning Ziyu Liu Shengyuan Hu Zhiwei Steven Wu Virginia Smith FedML 22 51 0 16 Jun 2022
Federated learning: Applications, challenges and future directions Subrato Bharati Hossain Mondal Prajoy Podder V. B. Surya Prasath FedML 39 53 0 18 May 2022
Secure Distributed/Federated Learning: Prediction-Privacy Trade-Off for Multi-Agent System Mohamed Ridha Znaidi Gaurav Gupta P. Bogdan FedML 6 1 0 24 Apr 2022
Federated Learning from Only Unlabeled Data with Class-Conditional-Sharing Clients Nan Lu Zhao Wang Xiaoxiao Li Gang Niu Qianming Dou Masashi Sugiyama FedML 27 39 0 07 Apr 2022
Learning Predictions for Algorithms with Predictions M. Khodak Maria-Florina Balcan Ameet Talwalkar Sergei Vassilvitskii 17 25 0 18 Feb 2022
Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning A. Bietti Chen-Yu Wei Miroslav Dudík John Langford Zhiwei Steven Wu FedML 20 43 0 10 Feb 2022
Transfer Learning In Differential Privacy's Hybrid-Model Reʾuven Kohen Or Sheffet 21 6 0 28 Jan 2022
The Internet of Federated Things (IoFT): A Vision for the Future and In-depth Survey of Data-driven Approaches for Federated Learning Raed Al Kontar Naichen Shi Xubo Yue Seokhyun Chung E. Byon ... C. Okwudire Garvesh Raskutti R. Saigal Karandeep Singh Ye Zhisheng FedML 36 50 0 09 Nov 2021
PRECAD: Privacy-Preserving and Robust Federated Learning via Crypto-Aided Differential Privacy Xiaolan Gu Ming Li Lishuang Xiong FedML 18 10 0 22 Oct 2021
Private Multi-Task Learning: Formulation and Applications to Federated Learning Shengyuan Hu Zhiwei Steven Wu Virginia Smith FedML 27 19 0 30 Aug 2021
Learning-to-learn non-convex piecewise-Lipschitz functions Maria-Florina Balcan M. Khodak Dravyansh Sharma Ameet Talwalkar 19 13 0 19 Aug 2021
Efficient Federated Meta-Learning over Multi-Access Wireless Networks Sheng Yue Ju Ren Jiang Xin Deyu Zhang Yaoxue Zhang W. Zhuang 15 38 0 14 Aug 2021
Privacy-Preserving Machine Learning: Methods, Challenges and Directions Runhua Xu Nathalie Baracaldo J. Joshi 29 100 0 10 Aug 2021
A Field Guide to Federated Optimization Jianyu Wang Zachary B. Charles Zheng Xu Gauri Joshi H. B. McMahan ... Mi Zhang Tong Zhang Chunxiang Zheng Chen Zhu Wennan Zhu FedML 187 411 0 14 Jul 2021
Optimizing the Numbers of Queries and Replies in Federated Learning with Differential Privacy Yipeng Zhou Xuezheng Liu Yao Fu Di Wu Chao Li Shui Yu FedML 30 2 0 05 Jul 2021
Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing M. Khodak Renbo Tu Tian Li Liam Li Maria-Florina Balcan Virginia Smith Ameet Talwalkar FedML 35 78 0 08 Jun 2021
Federated Few-Shot Learning with Adversarial Learning Chenyou Fan Jianwei Huang FedML 13 29 0 01 Apr 2021
Federated $f$ -Differential Privacy Qinqing Zheng Shuxiao Chen Qi Long Weijie J. Su FedML 77 55 0 22 Feb 2021
Collaborative Federated Learning For Healthcare: Multi-Modal COVID-19 Diagnosis at the Edge A. Qayyum Kashif Ahmad Muhammad Ahtazaz Ahsan Ala I. Al-Fuqaha Junaid Qadir FedML 30 187 0 19 Jan 2021
On the Practicality of Differential Privacy in Federated Learning by Tuning Iteration Times Yao Fu Yipeng Zhou Di Wu Shui Yu Yonggang Wen Chao Li FedML 24 9 0 11 Jan 2021
Privacy and Robustness in Federated Learning: Attacks and Defenses Lingjuan Lyu Han Yu Xingjun Ma Chen Chen Lichao Sun Jun Zhao Qiang Yang Philip S. Yu FedML 183 355 0 07 Dec 2020
SoK: Training Machine Learning Models over Multiple Sources with Privacy Preservation Lushan Song Guopeng Lin Jiaxuan Wang Haoqi Wu Wenqiang Ruan Weili Han 29 9 0 06 Dec 2020
A Comprehensive Survey on Local Differential Privacy Toward Data Statistics and Analysis Teng Wang Xuefeng Zhang Xuefeng Zhang Xinyu Yang 14 86 0 11 Oct 2020
More Than Privacy: Applying Differential Privacy in Key Areas of Artificial Intelligence Tianqing Zhu Dayong Ye Wei Wang Wanlei Zhou Philip S. Yu SyDa 34 125 0 05 Aug 2020
A Systematic Literature Review on Federated Machine Learning: From A Software Engineering Perspective Sin Kit Lo Qinghua Lu Chen Wang Hye-Young Paik Liming Zhu FedML 45 83 0 22 Jul 2020
Robust Federated Learning: The Case of Affine Distribution Shifts Amirhossein Reisizadeh Farzan Farnia Ramtin Pedarsani Ali Jadbabaie FedML OOD 32 162 0 16 Jun 2020
GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators Dingfan Chen Tribhuvanesh Orekondy Mario Fritz SyDa 12 183 0 15 Jun 2020
Backdoor Attacks on Federated Meta-Learning Chien-Lun Chen L. Golubchik Marco Paolieri FedML 6 32 0 12 Jun 2020
A Comprehensive Overview and Survey of Recent Advances in Meta-Learning Huimin Peng VLM OffRL 14 35 0 17 Apr 2020
Personalized Federated Learning: A Meta-Learning Approach Alireza Fallah Aryan Mokhtari Asuman Ozdaglar FedML 36 561 0 19 Feb 2020
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 74 6,069 0 10 Dec 2019
Federated Learning with Differential Privacy: Algorithms and Performance Analysis Kang Wei Jun Li Ming Ding Chuan Ma H. Yang Farokhi Farhad Shi Jin Tony Q. S. Quek H. Vincent Poor FedML 18 1,561 0 01 Nov 2019
Federated Learning: Challenges, Methods, and Future Directions Tian Li Anit Kumar Sahu Ameet Talwalkar Virginia Smith FedML 30 4,414 0 21 Aug 2019
SoK: Differential Privacies Damien Desfontaines Balázs Pejó 31 121 0 04 Jun 2019
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 338 11,684 0 09 Mar 2017
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 139 1,199 0 16 Aug 2016