Divergence-aware Federated Self-Supervised Learning

9 April 2022

Papers citing "Divergence-aware Federated Self-Supervised Learning"

50 / 70 papers shown

Title
FSSUAVL: A Discriminative Framework using Vision Models for Federated Self-Supervised Audio and Image Understanding Yasar Abbas Ur Rehman Kin Wai Lau Yuyang Xie Ma Lan Jiajun Shen 34 0 0 13 Apr 2025
Federated Self-Supervised Learning for One-Shot Cross-Modal and Cross-Imaging Technique Segmentation Siladittya Manna Suresh Das Sayantari Ghosh Saumik Bhattacharya FedML 48 0 0 30 Mar 2025
SAFE: Self-Adjustment Federated Learning Framework for Remote Sensing Collaborative Perception Xiaohe Li Haohua Wu Jiahao Li Zide Fan Kaixin Zhang Xinming Li Yunping Ge Xinyu Zhao 32 1 0 25 Mar 2025
You Are Your Own Best Teacher: Achieving Centralized-level Performance in Federated Learning under Heterogeneous and Long-tailed Data Shanshan Yan Zexi Li Chao-Xiang Wu Meng Pang Yang Lu Yan Yan Hanzi Wang FedML 61 0 0 10 Mar 2025
Calibre: Towards Fair and Accurate Personalized Federated Learning with Self-Supervised Learning Sijia Chen Ningxin Su Baochun Li FedML 40 0 0 31 Dec 2024
ParallelSFL: A Novel Split Federated Learning Framework Tackling Heterogeneity Issues Yunming Liao Yang Xu Hongli Xu Zhiwei Yao Liusheng Huang C. Qiao FedML 45 6 0 02 Oct 2024
COALA: A Practical and Vision-Centric Federated Learning Platform Weiming Zhuang Jian Xu Chen Chen Jingtao Li Lingjuan Lyu VLM FedML 79 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 63 0 0 14 Jul 2024
A deep cut into Split Federated Self-supervised Learning Marcin Przewiȩźlikowski Marcin Osial Bartosz Zieliñski Marek 'Smieja FedML 40 0 0 12 Jun 2024
Federated Unsupervised Domain Generalization using Global and Local Alignment of Gradients Farhad Pourpanah Mahdiyar Molahasani Milad Soltany Michael A. Greenspan Ali Etemad FedML OOD 110 2 0 25 May 2024
EmInspector: Combating Backdoor Attacks in Federated Self-Supervised Learning Through Embedding Inspection Yuwen Qian Shuchi Wu Kang Wei Ming Ding Di Xiao Tao Xiang Chuan Ma Song Guo FedML AAML 40 0 0 21 May 2024
Generalized Cauchy-Schwarz Divergence and Its Deep Learning Applications Mingfei Lu Chenxu Li Shujian Yu Robert Jenssen Badong Chen 35 0 0 07 May 2024
FedSC: Provable Federated Self-supervised Learning with Spectral Contrastive Objective over Non-i.i.d. Data Shusen Jing Anlan Yu Shuai Zhang Songyang Zhang FedML 31 1 0 07 May 2024
A Mutual Information Perspective on Federated Contrastive Learning Christos Louizos M. Reisser Denis Korzhenkov SSL FedML 32 2 0 03 May 2024
Unsupervised Federated Optimization at the Edge: D2D-Enabled Learning without Labels Satyavrat Wagle Seyyedali Hosseinalipour Naji Khosravan Christopher G. Brinton FedML 40 2 0 15 Apr 2024
Rethinking the Representation in Federated Unsupervised Learning with Non-IID Data Xinting Liao Weiming Liu Chaochao Chen Pengyang Zhou Fengyuan Yu Huabin Zhu Binhui Yao Tao Wang Xiaolin Zheng Yanchao Tan FedML 51 7 0 25 Mar 2024
FedMef: Towards Memory-efficient Federated Dynamic Pruning Hong Huang Weiming Zhuang Chen Chen Lingjuan Lyu 62 7 0 21 Mar 2024
Membership Information Leakage in Federated Contrastive Learning Kongyang Chen Wenfeng Wang Zixin Wang Wangjun Zhang Zhipeng Li Yao Huang FedML 30 1 0 06 Mar 2024
Robust Training of Federated Models with Extremely Label Deficiency Yonggang Zhang Zhiqin Yang Xinmei Tian Nannan Wang Tongliang Liu Bo Han FedML 41 6 0 22 Feb 2024
Federated Learning with New Knowledge: Fundamentals, Advances, and Futures Lixu Wang Yang Zhao Jiahua Dong Ating Yin Qinbin Li Tianlin Li Dusit Niyato Qi Zhu FedML 79 2 0 03 Feb 2024
LW-FedSSL: Resource-efficient Layer-wise Federated Self-supervised Learning Ye Lin Tun Chu Myaet Thwal Le Quang Huy Minh N. H. Nguyen Choong Seon Hong FedML 40 2 0 22 Jan 2024
CCFC: Bridging Federated Clustering and Contrastive Learning Jie Yan Jing Liu Zhonghan Zhang FedML 46 3 0 12 Jan 2024
Relaxed Contrastive Learning for Federated Learning Seonguk Seo Jinkyu Kim Geeho Kim Bohyung Han FedML 42 8 0 10 Jan 2024
Harnessing the Power of Federated Learning in Federated Contextual Bandits Chengshuai Shi Ruida Zhou Kun Yang Cong Shen FedML 21 0 0 26 Dec 2023
Fed-QSSL: A Framework for Personalized Federated Learning under Bitwidth and Data Heterogeneity Yiyue Chen H. Vikalo C. Wang FedML 44 5 0 20 Dec 2023
MergeSFL: Split Federated Learning with Feature Merging and Batch Size Regulation Yunming Liao Yang Xu Hong-Ze Xu Lun Wang Zhiwei Yao C. Qiao FedML MoMe 38 10 0 22 Nov 2023
Federated Self-Supervised Learning of Monocular Depth Estimators for Autonomous Vehicles Elton F. S. Soares Carlos Alberto V. Campos MDE FedML 32 2 0 07 Oct 2023
BAGEL: Backdoor Attacks against Federated Contrastive Learning Yao Huang Kongyang Chen Jiannong Cao Jiaxing Shen Shaowei Wang Yun Peng Weilong Peng Kechao Cai FedML 34 3 0 14 Sep 2023
Tackling the Non-IID Issue in Heterogeneous Federated Learning by Gradient Harmonization Xinyu Zhang Weiyu Sun Ying-Cong Chen FedML 36 5 0 13 Sep 2023
Federated Learning for Large-Scale Scene Modeling with Neural Radiance Fields Teppei Suzuki AI4CE 26 8 0 12 Sep 2023
Fast FixMatch: Faster Semi-Supervised Learning with Curriculum Batch Size John Chen Chen Dun Anastasios Kyrillidis 21 2 0 07 Sep 2023
Federated Learning for Computer Vision Yassine Himeur Iraklis Varlamis Hamza Kheddar Abbes Amira Shadi Atalla Yashbir Singh F. Bensaali W. Mansoor FedML 26 20 0 24 Aug 2023
MAS: Towards Resource-Efficient Federated Multiple-Task Learning Weiming Zhuang Yonggang Wen Lingjuan Lyu Shuai Zhang FedML 30 15 0 21 Jul 2023
L-DAWA: Layer-wise Divergence Aware Weight Aggregation in Federated Self-Supervised Visual Representation Learning Yasar Abbas Ur Rehman Yan Gao Pedro Gusmão Mina Alibeigi Jiajun Shen Nicholas D. Lane FedML 40 18 0 14 Jul 2023
Combating Data Imbalances in Federated Semi-supervised Learning with Dual Regulators Sikai Bai Shuaicheng Li Weiming Zhuang Jie Zhang Song Guo Kunlin Yang Jun Hou Shuai Zhang Junyu Gao Shuai Yi FedML 29 6 0 11 Jul 2023
When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions Weiming Zhuang Chen Chen Lingjuan Lyu Chong Chen Yaochu Jin Lingjuan Lyu AIFin AI4CE 99 85 0 27 Jun 2023
FSAR: Federated Skeleton-based Action Recognition with Adaptive Topology Structure and Knowledge Distillation Jingwen Guo Hong Liu Shitong Sun Tianyu Guo Hao Fei Chenyang Si 41 3 0 19 Jun 2023
FedWon: Triumphing Multi-domain Federated Learning Without Normalization Weiming Zhuang Lingjuan Lyu 19 9 0 09 Jun 2023
Personalized Federated Learning under Mixture of Distributions Yue Wu Shuaicheng Zhang Wenchao Yu Yanchi Liu Quanquan Gu Dawei Zhou Haifeng Chen Wei Cheng FedML 74 39 0 01 May 2023
Federated Learning without Full Labels: A Survey Yilun Jin Yang Liu Kai Chen Qian Yang FedML 12 26 0 25 Mar 2023
Re-thinking Federated Active Learning based on Inter-class Diversity Sangmook Kim Sangmin Bae Hwanjun Song Se-Young Yun FedML 33 14 0 22 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
FedIL: Federated Incremental Learning from Decentralized Unlabeled Data with Convergence Analysis Nan Yang Dong Yuan Charles Z. Liu Yong Deng Wei Bao FedML 66 5 0 23 Feb 2023
A Comprehensive Review and a Taxonomy of Edge Machine Learning: Requirements, Paradigms, and Techniques Wenbin Li Hakim Hacid Ebtesam Almazrouei Merouane Debbah 34 13 0 16 Feb 2023
Self-supervised On-device Federated Learning from Unlabeled Streams Jiahe Shi Yawen Wu Dewen Zeng Jun Tao Jingtong Hu Yiyu Shi FedML 19 5 0 02 Dec 2022
Feature Correlation-guided Knowledge Transfer for Federated Self-supervised Learning Yi Liu Song Guo Jie Zhang Qihua Zhou Yingchun Wang Xiaohan Zhao 22 1 0 14 Nov 2022
Federated Graph Representation Learning using Self-Supervision Susheel Suresh Daniel Godbout Arko Provo Mukherjee Mayank Shrivastava Jennifer Neville Pan Li OOD FedML 38 2 0 27 Oct 2022
PATS: Sensitivity-aware Noisy Learning for Pretrained Language Models Yupeng Zhang Hongzhi Zhang Sirui Wang Wei Wu Zhoujun Li AAML 33 1 0 22 Oct 2022
Does Learning from Decentralized Non-IID Unlabeled Data Benefit from Self Supervision? Lirui Wang Kaipeng Zhang Yunzhu Li Yonglong Tian Russ Tedrake 34 16 0 20 Oct 2022
Federated Training of Dual Encoding Models on Small Non-IID Client Datasets Raviteja Vemulapalli Warren Morningstar Philip Mansfield Hubert Eichner K. Singhal Arash Afkanpour Bradley Green FedML 39 2 0 30 Sep 2022