Distillation-Based Semi-Supervised Federated Learning for Communication-Efficient Collaborative Training with Non-IID Private Data

14 August 2020

Papers citing "Distillation-Based Semi-Supervised Federated Learning for Communication-Efficient Collaborative Training with Non-IID Private Data"

35 / 35 papers shown

Title
Soft-Label Caching and Sharpening for Communication-Efficient Federated Distillation Kitsuya Azuma Takayuki Nishio Yuichi Kitagawa Wakako Nakano Takahito Tanimura FedML 70 0 0 28 Apr 2025
Privacy-Preserving Federated Embedding Learning for Localized Retrieval-Augmented Generation Qianren Mao Qili Zhang Hanwen Hao Zhentao Han Runhua Xu ... Jing Chen Yangqiu Song Jin Dong Jianxin Li Philip S. Yu 71 1 0 27 Apr 2025
Intelligent Attacks and Defense Methods in Federated Learning-enabled Energy-Efficient Wireless Networks Han Zhang Hao Zhou Medhat H. M. Elsayed Majid Bavand Raimundas Gaigalas Yigit Ozcan Melike Erol-Kantarci AAML 72 0 0 25 Apr 2025
Moss: Proxy Model-based Full-Weight Aggregation in Federated Learning with Heterogeneous Models Y. Cai Ziqi Zhang Ding Li Yao Guo Xiangqun Chen 55 0 0 13 Mar 2025
dFLMoE: Decentralized Federated Learning via Mixture of Experts for Medical Data Analysis Luyuan Xie Tianyu Luan Wenyuan Cai Guochen Yan Zhe Chen Nan Xi Yuejian Fang Qingni Shen Zhonghai Wu Junsong Yuan FedML 67 0 0 13 Mar 2025
FedDr+: Stabilizing Dot-regression with Global Feature Distillation for Federated Learning Seongyoon Kim Minchan Jeong Sungnyun Kim Sungwoo Cho Sumyeong Ahn Se-Young Yun FedML 47 0 0 04 Jun 2024
Federated Model Heterogeneous Matryoshka Representation Learning Liping Yi Han Yu Chao Ren Gang Wang Xiaoguang Liu Xiaoxiao Li FedML 43 8 0 01 Jun 2024
FeDeRA:Efficient Fine-tuning of Language Models in Federated Learning Leveraging Weight Decomposition Yuxuan Yan Qianqian Yang Shunpu Tang Zhiguo Shi 38 13 0 29 Apr 2024
Multiple Access in the Era of Distributed Computing and Edge Intelligence Nikos G. Evgenidis Nikos A. Mitsiou Vasiliki I. Koutsioumpa Sotiris A. Tegos P. Diamantoulakis G. Karagiannidis 41 8 0 26 Feb 2024
Practical Insights into Knowledge Distillation for Pre-Trained Models Norah Alballa Marco Canini 48 2 0 22 Feb 2024
Distributed Personalized Empirical Risk Minimization Yuyang Deng Mohammad Mahdi Kamani Pouria Mahdavinia M. Mahdavi 31 4 0 26 Oct 2023
$Λ$ -Split: A Privacy-Preserving Split Computing Framework for Cloud-Powered Generative AI Shoki Ohta Takayuki Nishio 64 4 0 23 Oct 2023
Teacher-Student Architecture for Knowledge Distillation: A Survey Chengming Hu Xuan Li Danyang Liu Haolun Wu Xi Chen Ju Wang Xue Liu 21 16 0 08 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 43 23 0 20 Jul 2023
FedMultimodal: A Benchmark For Multimodal Federated Learning Tiantian Feng Digbalay Bose Tuo Zhang Rajat Hebbar Anil Ramakrishna Rahul Gupta Mi Zhang Salman Avestimehr Shrikanth Narayanan 32 48 0 15 Jun 2023
Homogenizing Non-IID datasets via In-Distribution Knowledge Distillation for Decentralized Learning Deepak Ravikumar Gobinda Saha Sai Aparna Aketi Kaushik Roy 18 1 0 09 Apr 2023
Knowledge Distillation in Federated Edge Learning: A Survey Zhiyuan Wu Sheng Sun Yuwei Wang Min Liu Xue Jiang Runhan Li Bo Gao FedML 27 4 0 14 Jan 2023
FedICT: Federated Multi-task Distillation for Multi-access Edge Computing Zhiyuan Wu Sheng Sun Yuwei Wang Min Liu Quyang Pan Xue Jiang Bo Gao 35 31 0 01 Jan 2023
Decentralized Learning with Multi-Headed Distillation A. Zhmoginov Mark Sandler Nolan Miller Gus Kristiansen Max Vladymyrov FedML 37 4 0 28 Nov 2022
Scalable Collaborative Learning via Representation Sharing Frédéric Berdoz Abhishek Singh Martin Jaggi Ramesh Raskar FedML 22 3 0 20 Nov 2022
Federated Learning for Medical Applications: A Taxonomy, Current Trends, Challenges, and Future Research Directions A. Rauniyar D. Hagos Debesh Jha J. E. Haakegaard Ulas Bagci D. Rawat Vladimir Vlassov OOD 43 90 0 05 Aug 2022
Towards Efficient Communications in Federated Learning: A Contemporary Survey Zihao Zhao Yuzhu Mao Yang Liu Linqi Song Ouyang Ye Xinlei Chen Wenbo Ding FedML 54 59 0 02 Aug 2022
Federated Distillation based Indoor Localization for IoT Networks Yaya Etiabi Marwa Chafii El-Mehdi Amhoud FedML 40 15 0 23 May 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
TinyMLOps: Operational Challenges for Widespread Edge AI Adoption Sam Leroux Pieter Simoens Meelis Lootus Kartik Thakore Akshay Sharma 24 16 0 21 Mar 2022
Communication-Efficient Federated Distillation with Active Data Sampling Lumin Liu Jun Zhang Shenghui Song Khaled B. Letaief FedML 21 25 0 14 Mar 2022
An Efficient Federated Distillation Learning System for Multi-task Time Series Classification Huanlai Xing Zhiwen Xiao R. Qu Zonghai Zhu Bowen Zhao FedML 35 108 0 30 Dec 2021
Efficient Federated Learning for AIoT Applications Using Knowledge Distillation Tian Liu Xian Wei Jun Xia Xin Fu Ting Wang Mingsong Chen 6 15 0 29 Nov 2021
Semi-Supervised Federated Learning with non-IID Data: Algorithm and System Design Zhe Zhang Shiyao Ma Jiangtian Nie Yi Wu Qiang Yan Xiaoke Xu Dusit Niyato FedML 13 16 0 26 Oct 2021
SSFL: Tackling Label Deficiency in Federated Learning via Personalized Self-Supervision Chaoyang He Zhengyu Yang Erum Mushtaq Sunwoo Lee Mahdi Soltanolkotabi A. Avestimehr FedML 98 36 0 06 Oct 2021
Personalized Federated Learning for Heterogeneous Clients with Clustered Knowledge Transfer Yae Jee Cho Jianyu Wang Tarun Chiruvolu Gauri Joshi FedML 35 30 0 16 Sep 2021
FedZKT: Zero-Shot Knowledge Transfer towards Resource-Constrained Federated Learning with Heterogeneous On-Device Models Lan Zhang Dapeng Oliver Wu Xiaoyong Yuan FedML 38 47 0 08 Sep 2021
Reward-Based 1-bit Compressed Federated Distillation on Blockchain Leon Witt Usama Zafar KuoYeh Shen Felix Sattler Dan Li Wojciech Samek FedML 35 4 0 27 Jun 2021
Improving Semi-supervised Federated Learning by Reducing the Gradient Diversity of Models Zhengming Zhang Yaoqing Yang Z. Yao Yujun Yan Joseph E. Gonzalez Michael W. Mahoney FedML 39 36 0 26 Aug 2020
Large scale distributed neural network training through online distillation Rohan Anil Gabriel Pereyra Alexandre Passos Róbert Ormándi George E. Dahl Geoffrey E. Hinton FedML 278 404 0 09 Apr 2018