Preserving Privacy in Federated Learning with Ensemble Cross-Domain Knowledge Distillation

10 September 2022

Ziyan Wu

Papers citing "Preserving Privacy in Federated Learning with Ensemble Cross-Domain Knowledge Distillation"

38 / 38 papers shown

Title
Avoid Forgetting by Preserving Global Knowledge Gradients in Federated Learning with Non-IID Data Abhijit Chunduru Majid Morafah Mahdi Morafah Vishnu Pandi Chellapandi Ang Li FedML 49 0 0 26 May 2025
FedSaaS: Class-Consistency Federated Semantic Segmentation via Global Prototype Supervision and Local Adversarial Harmonization Xiaoyang Yu Xiaoming Wu Xin Wang Dongrun Li Ming Yang Peng Cheng 58 0 0 14 May 2025
Soft-Label Caching and Sharpening for Communication-Efficient Federated Distillation Kitsuya Azuma Takayuki Nishio Yuichi Kitagawa Wakako Nakano Takahito Tanimura FedML 177 0 0 28 Apr 2025
Towards Harnessing the Collaborative Power of Large and Small Models for Domain Tasks Yang Liu Bingjie Yan Tianyuan Zou Jianqing Zhang Zixuan Gu ... Jiajian Li Xiaozhou Ye Ye Ouyang Qiang Yang Yanzhe Zhang ALM 453 1 0 24 Apr 2025
Corrected with the Latest Version: Make Robust Asynchronous Federated Learning Possible Chaoyi Lu Yiding Sun Pengbo Li Zhichuan Yang FedML 119 1 0 05 Apr 2025
FedBEns: One-Shot Federated Learning based on Bayesian Ensemble Jacopo Talpini Marco Savi Giovanni Neglia FedML Presented at ResearchTrend Connect \| FedML on 07 May 2025 145 0 0 19 Mar 2025
dFLMoE: Decentralized Federated Learning via Mixture of Experts for Medical Data Analysis Luyuan Xie Tianyu Luan Wenyuan Cai Guochen Yan Zhaoyu Chen Nan Xi Yuejian Fang Qingni Shen Zhonghai Wu Junsong Yuan FedML 315 0 0 13 Mar 2025
Data-Free Black-Box Federated Learning via Zeroth-Order Gradient Estimation Xinge Ma Jin Wang Xuejie Zhang FedML 130 0 0 08 Mar 2025
One-shot Federated Learning Methods: A Practical Guide Xiang Liu Zhenheng Tang Xia Li Yijun Song Sijie Ji Zemin Liu Bo Han Linshan Jiang Jialin Li FedML 171 1 0 13 Feb 2025
DFDG: Data-Free Dual-Generator Adversarial Distillation for One-Shot Federated Learning Kangyang Luo Shuai Wang Y. Fu Renrong Shao Xiang Li Yunshi Lan Ming Gao Jinlong Shu FedML 111 3 0 12 Sep 2024
Privacy-Preserving Federated Learning with Consistency via Knowledge Distillation Using Conditional Generator Kangyang Luo Shuai Wang Xiang Li Yunshi Lan Ming Gao Jinlong Shu FedML 77 2 0 11 Sep 2024
FedTSA: A Cluster-based Two-Stage Aggregation Method for Model-heterogeneous Federated Learning Boyu Fan Chenrui Wu Xiang Su Pan Hui FedML 108 3 0 06 Jul 2024
Linkage on Security, Privacy and Fairness in Federated Learning: New Balances and New Perspectives Linlin Wang Tianqing Zhu Wanlei Zhou Philip S. Yu 65 2 0 16 Jun 2024
Harnessing Increased Client Participation with Cohort-Parallel Federated Learning Akash Dhasade Anne-Marie Kermarrec Tuan-Anh Nguyen Rafael Pires M. Vos FedML 149 0 0 24 May 2024
Overcoming Data and Model Heterogeneities in Decentralized Federated Learning via Synthetic Anchors Chun-Yin Huang Kartik Srinivas Xin Zhang Xiaoxiao Li DD 136 7 0 19 May 2024
Beyond Noise: Privacy-Preserving Decentralized Learning with Virtual Nodes Sayan Biswas Mathieu Even Anne-Marie Kermarrec Laurent Massoulie Rafael Pires Rishi Sharma M. Vos 76 3 0 15 Apr 2024
Federated Distillation: A Survey Lin Li Jianping Gou Baosheng Yu Lan Du Zhang Yiand Dacheng Tao DD FedML 115 8 0 02 Apr 2024
A Comprehensive Survey of Federated Transfer Learning: Challenges, Methods and Applications Wei Guo Fuzhen Zhuang Xiao Zhang Yiqi Tong Jin Dong FedML 90 19 0 03 Mar 2024
On the Byzantine-Resilience of Distillation-Based Federated Learning Christophe Roux Max Zimmer Sebastian Pokutta AAML 150 1 0 19 Feb 2024
Direct Distillation between Different Domains Jialiang Tang Shuo Chen Gang Niu Hongyuan Zhu Qiufeng Wang Chen Gong Masashi Sugiyama 128 3 0 12 Jan 2024
Federated Learning via Input-Output Collaborative Distillation Xuan Gong Shanglin Li Yuxiang Bao Barry Yao Yawen Huang Ziyan Wu Baochang Zhang Yefeng Zheng David Doermann FedML 71 6 0 22 Dec 2023
Eliminating Domain Bias for Federated Learning in Representation Space Jianqing Zhang Yang Hua Jian Cao Hao Wang Tao Song Zhengui Xue Ruhui Ma Haibing Guan FedML 113 35 0 25 Nov 2023
Little is Enough: Improving Privacy by Sharing Labels in Federated Semi-Supervised Learning Amr Abourayya Jens Kleesiek Kanishka Rao Erman Ayday Bharat Rao Geoff Webb Michael Kamp FedML 67 0 0 09 Oct 2023
REFT: Resource-Efficient Federated Training Framework for Heterogeneous and Resource-Constrained Environments Humaid Ahmed Desai Amr B. Hilal Hoda Eldardiry 49 0 0 25 Aug 2023
Heterogeneous Federated Learning via Personalized Generative Networks Zahra Taghiyarrenani Abdallah S. Abdallah Sławomir Nowaczyk Sepideh Pashami FedML 63 0 0 25 Aug 2023
Communication-Efficient Search under Fully Homomorphic Encryption for Federated Machine Learning Dongfang Zhao FedML 77 1 0 09 Aug 2023
A Survey of What to Share in Federated Learning: Perspectives on Model Utility, Privacy Leakage, and Communication Efficiency Jiawei Shao Zijian Li Wenqiang Sun Tailin Zhou Yuchang Sun Lumin Liu Zehong Lin Yuyi Mao Jun Zhang FedML 109 28 0 20 Jul 2023
Towards Open Federated Learning Platforms: Survey and Vision from Technical and Legal Perspectives Moming Duan Qinbin Li Linshan Jiang Bingsheng He FedML 98 5 0 05 Jul 2023
Federated Generative Learning with Foundation Models Jie Zhang Xiaohua Qi Bo Zhao FedML 116 22 0 28 Jun 2023
FedPDD: A Privacy-preserving Double Distillation Framework for Cross-silo Federated Recommendation Sheng Wan Dashan Gao Hanlin Gu Daning Hu FedML 58 7 0 09 May 2023
Model-Contrastive Federated Domain Adaptation Chang’an Yi Haotian Chen Yonghui Xu Yifan Zhang MedIm FedML 57 0 0 07 May 2023
Federated Learning over Coupled Graphs Runze Lei Peijie Wang Junzhou Zhao Lin Lan Jing Tao Chao Deng Junlan Feng Xidian Wang Xiaohong Guan FedML 99 15 0 26 Jan 2023
Decentralized Learning with Multi-Headed Distillation A. Zhmoginov Mark Sandler Nolan Miller Gus Kristiansen Max Vladymyrov FedML 75 4 0 28 Nov 2022
A Survey on Heterogeneous Federated Learning Dashan Gao Xin Yao Qian Yang FedML 99 63 0 10 Oct 2022
Domain Discrepancy Aware Distillation for Model Aggregation in Federated Learning Shangchao Su Bin Li Xiangyang Xue FedML 69 1 0 04 Oct 2022
Reducing Impacts of System Heterogeneity in Federated Learning using Weight Update Magnitudes Irene Wang 78 1 0 30 Aug 2022
FEL: High Capacity Learning for Recommendation and Ranking via Federated Ensemble Learning Meisam Hejazinia Dzmitry Huba Ilias Leontiadis Kiwan Maeng Mani Malek Luca Melis Ilya Mironov Milad Nasr Kaikai Wang Carole-Jean Wu FedML 72 6 0 07 Jun 2022
FRAug: Tackling Federated Learning with Non-IID Features via Representation Augmentation Haokun Chen A. Frikha Denis Krompass Jindong Gu Volker Tresp OOD 83 26 0 30 May 2022