RSCFed: Random Sampling Consensus Federated Semi-supervised Learning

26 March 2022

Papers citing "RSCFed: Random Sampling Consensus Federated Semi-supervised Learning"

28 / 28 papers shown

Title
Federated Source-free Domain Adaptation for Classification: Weighted Cluster Aggregation for Unlabeled Data Junki Mori Kosuke Kihara Taiki Miyagawa Akinori F. Ebihara Isamu Teranishi Hisashi Kashima 76 1 0 18 Dec 2024
(FL) $^2$ : Overcoming Few Labels in Federated Semi-Supervised Learning Seungjoo Lee Thanh-Long V. Le Jaemin Shin Sung-Ju Lee FedML 34 1 0 30 Oct 2024
COALA: A Practical and Vision-Centric Federated Learning Platform Weiming Zhuang Jian Xu Chen Chen Jingtao Li Lingjuan Lyu VLM FedML 72 4 0 23 Jul 2024
Learning Unlabeled Clients Divergence via Anchor Model Aggregation for Federated Semi-supervised Learning Marawan Elbatel Hualiang Wang Jixiang Chen Hao Wang Xiaomeng Li FedML 55 0 0 14 Jul 2024
FedMLP: Federated Multi-Label Medical Image Classification under Task Heterogeneity Zhaobin Sun Nannan Wu Junjie Shi Li Yu Xin Yang Kwang-Ting Cheng Zengqiang Yan 21 0 0 27 Jun 2024
Estimating before Debiasing: A Bayesian Approach to Detaching Prior Bias in Federated Semi-Supervised Learning Guogang Zhu Xuefeng Liu Xinghao Wu Shaojie Tang Chao Tang Jianwei Niu Hao Su FedML 47 1 0 30 May 2024
A Mutual Information Perspective on Federated Contrastive Learning Christos Louizos M. Reisser Denis Korzhenkov SSL FedML 30 2 0 03 May 2024
Robust Training of Federated Models with Extremely Label Deficiency Yonggang Zhang Zhiqin Yang Xinmei Tian Nannan Wang Tongliang Liu Bo Han FedML 29 6 0 22 Feb 2024
Rethinking Semi-Supervised Federated Learning: How to co-train fully-labeled and fully-unlabeled client imaging data Pramit Saha Divyanshu Mishra J. A. Noble FedML 35 8 0 28 Oct 2023
Local or Global: Selective Knowledge Assimilation for Federated Learning with Limited Labels Yae Jee Cho Gauri Joshi Dimitrios Dimitriadis FedML 19 4 0 17 Jul 2023
Combating Data Imbalances in Federated Semi-supervised Learning with Dual Regulators Sikai Bai Shuaicheng Li Weiming Zhuang Jie M. Zhang Song Guo Kunlin Yang Jun Hou Shuai Zhang Junyu Gao Shuai Yi FedML 24 6 0 11 Jul 2023
Towards Open Federated Learning Platforms: Survey and Vision from Technical and Legal Perspectives Moming Duan Qinbin Li Linshan Jiang Bingsheng He FedML 28 4 0 05 Jul 2023
FedNoRo: Towards Noise-Robust Federated Learning by Addressing Class Imbalance and Label Noise Heterogeneity Nannan Wu Li Yu Xue Jiang Kwang-Ting Cheng Zengqiang Yan FedML 28 36 0 09 May 2023
Exploring One-shot Semi-supervised Federated Learning with A Pre-trained Diffusion Model Min Yang Shangchao Su Bin Li Xiangyang Xue DiffM 19 29 0 06 May 2023
Towards Unbiased Training in Federated Open-world Semi-supervised Learning Jie M. Zhang Xiaosong Ma Song Guo Wenchao Xu FedML 22 8 0 01 May 2023
Federated Learning without Full Labels: A Survey Yilun Jin Yang Liu Kai Chen Qian Yang FedML 10 26 0 25 Mar 2023
FedMAE: Federated Self-Supervised Learning with One-Block Masked Auto-Encoder Nan Yang Xuanyu Chen Charles Z. Liu Dong Yuan Wei Bao Li-zhen Cui 35 2 0 20 Mar 2023
Federated Semi-Supervised Learning with Annotation Heterogeneity Xinyi Shang Gang Huang Yang Lu Jian Lou Bo Han Y. Cheung Hanzi Wang FedML 41 1 0 04 Mar 2023
FedIL: Federated Incremental Learning from Decentralized Unlabeled Data with Convergence Analysis Nan Yang Dong Yuan Charles Z. Liu Yong Deng Wei Bao FedML 58 5 0 23 Feb 2023
Dual Class-Aware Contrastive Federated Semi-Supervised Learning Qianling Guo Yong Qi Saiyu Qi Di Wu FedML 21 5 0 16 Nov 2022
Cross-client Label Propagation for Transductive and Semi-Supervised Federated Learning Jonathan Scott Michelle Yeo Christoph H. Lampert FedML 14 0 0 12 Oct 2022
Calibrating Label Distribution for Class-Imbalanced Barely-Supervised Knee Segmentation Yiqun Lin Huifeng Yao Zezhong Li Guoyan Zheng X. Li 19 29 0 07 May 2022
Challenges and Approaches for Mitigating Byzantine Attacks in Federated Learning Junyu Shi Wei Wan Shengshan Hu Jianrong Lu L. Zhang AAML 22 74 0 29 Dec 2021
Specificity-Preserving Federated Learning for MR Image Reconstruction Chun-Mei Feng Yu-bao Yan Shanshan Wang Yong Xu Ling Shao H. Fu OOD 24 78 0 09 Dec 2021
Emerging Trends in Federated Learning: From Model Fusion to Federated X Learning Shaoxiong Ji Yue Tan Teemu Saravirta Zhiqin Yang Yixin Liu Lauri Vasankari Shirui Pan Guodong Long A. Walid FedML 31 76 0 25 Feb 2021
Federated Learning on Non-IID Data Silos: An Experimental Study Q. Li Yiqun Diao Quan Chen Bingsheng He FedML OOD 87 945 0 03 Feb 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 31 36 0 26 Aug 2020
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results Antti Tarvainen Harri Valpola OOD MoMe 261 1,275 0 06 Mar 2017