Emerging Trends in Federated Learning: From Model Fusion to Federated X Learning

25 February 2021

Papers citing "Emerging Trends in Federated Learning: From Model Fusion to Federated X Learning"

24 / 24 papers shown

Title
Knowledge Augmentation in Federation: Rethinking What Collaborative Learning Can Bring Back to Decentralized Data Wentai Wu Ligang He Saiqin Long Ahmed M. Abdelmoniem Yingliang Wu Rui Mao 50 0 0 05 Mar 2025
FedCLEAN: byzantine defense by CLustering Errors of Activation maps in Non-IID federated learning environments Mehdi Ben Ghali R. Bellafqira G. Coatrieux AAML FedML 41 0 0 21 Jan 2025
FedBrain-Distill: Communication-Efficient Federated Brain Tumor Classification Using Ensemble Knowledge Distillation on Non-IID Data Rasoul Jafari Gohari Laya Aliahmadipour Ezat Valipour FedML 21 0 0 09 Sep 2024
FedACK: Federated Adversarial Contrastive Knowledge Distillation for Cross-Lingual and Cross-Model Social Bot Detection Yingguang Yang Renyu Yang Hao Peng Yangyang Li Tong Li Yong Liao Pengyuan Zhou FedML 29 28 0 10 Mar 2023
Federated Semi-Supervised Learning with Annotation Heterogeneity Xinyi Shang Gang Huang Yang Lu Jian Lou Bo Han Y. Cheung Hanzi Wang FedML 25 1 0 04 Mar 2023
CADIS: Handling Cluster-skewed Non-IID Data in Federated Learning with Clustered Aggregation and Knowledge DIStilled Regularization Nang Hung Nguyen Duc Long Nguyen Trong Bang Nguyen T. Nguyen H. Pham Truong Thao Nguyen Phi Le Nguyen FedML 14 8 0 21 Feb 2023
Federated Reinforcement Learning for Real-Time Electric Vehicle Charging and Discharging Control Zixuan Zhang Yuning Jiang Yuanming Shi Ye Shi Wei Chen 39 13 0 04 Oct 2022
Sparse Random Networks for Communication-Efficient Federated Learning Berivan Isik Francesco Pase Deniz Gunduz Tsachy Weissman M. Zorzi FedML 70 52 0 30 Sep 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 27 89 0 05 Aug 2022
CalFAT: Calibrated Federated Adversarial Training with Label Skewness Chen Chen Yuchen Liu Xingjun Ma Lingjuan Lyu FedML 159 31 0 30 May 2022
Cali3F: Calibrated Fast Fair Federated Recommendation System Zhitao Zhu Shijing Si Jianzong Wang Jing Xiao FedML 60 14 0 26 May 2022
Communication Efficient Federated Learning for Generalized Linear Bandits Chuanhao Li Hongning Wang FedML 8 13 0 02 Feb 2022
Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification Yuxin Wen Jonas Geiping Liam H. Fowl Micah Goldblum Tom Goldstein FedML 71 91 0 01 Feb 2022
Personalized Federated Learning over non-IID Data for Indoor Localization Peng Wu Tales Imbiriba Junha Park Sunwoo Kim Pau Closas FedML 15 28 0 09 Jul 2021
Federated Multi-View Learning for Private Medical Data Integration and Analysis Sicong Che Hao Peng Lichao Sun Yong Chen Lifang He FedML 56 40 0 04 May 2021
FedProto: Federated Prototype Learning across Heterogeneous Clients Yue Tan Guodong Long Lu Liu Tianyi Zhou Qinghua Lu Jing Jiang Chengqi Zhang FedML 151 287 0 01 May 2021
Towards Personalized Federated Learning A. Tan Han Yu Li-zhen Cui Qiang Yang FedML AI4CE 180 832 0 01 Mar 2021
A New Look and Convergence Rate of Federated Multi-Task Learning with Laplacian Regularization Canh T. Dinh Thanh Tung Vu N. H. Tran Minh N. Dao Hongyu Zhang FedML 65 38 0 14 Feb 2021
FedCVT: Semi-supervised Vertical Federated Learning with Cross-view Training Yan Kang Yang Liu Xinle Liang FedML 60 50 0 25 Aug 2020
FedML: A Research Library and Benchmark for Federated Machine Learning Chaoyang He Songze Li Jinhyun So Xiao Zeng Mi Zhang ... Yang Liu Ramesh Raskar Qiang Yang M. Annavaram Salman Avestimehr FedML 162 553 0 27 Jul 2020
Adaptive Personalized Federated Learning Yuyang Deng Mohammad Mahdi Kamani M. Mahdavi FedML 183 535 0 30 Mar 2020
Improved Baselines with Momentum Contrastive Learning Xinlei Chen Haoqi Fan Ross B. Girshick Kaiming He SSL 238 3,359 0 09 Mar 2020
Threats to Federated Learning: A Survey Lingjuan Lyu Han Yu Qiang Yang FedML 186 427 0 04 Mar 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 243 11,568 0 09 Mar 2017