Fed2: Feature-Aligned Federated Learning

28 November 2021

Zirui Xu

Papers citing "Fed2: Feature-Aligned Federated Learning"

42 / 42 papers shown

Title
Can Textual Gradient Work in Federated Learning? Minghui Chen Ruinan Jin Wenlong Deng Yuanyuan Chen Zhi Huang Han Yu Xiaoxiao Li FedML 79 2 0 27 Feb 2025
The Transition from Centralized Machine Learning to Federated Learning for Mental Health in Education: A Survey of Current Methods and Future Directions Maryam Ebrahimi Rajeev Sahay Seyyedali Hosseinalipour Bita Akram 37 1 0 20 Jan 2025
Federated brain tumor segmentation: an extensive benchmark Matthis Manthe Stefan Duffner Carole Lartizien OOD FedML 30 4 0 07 Oct 2024
Weight Scope Alignment: A Frustratingly Easy Method for Model Merging Yichu Xu Xin-Chun Li Le Gan De-Chuan Zhan MoMe 29 0 0 22 Aug 2024
Federated Model Heterogeneous Matryoshka Representation Learning Liping Yi Han Yu Chao Ren Gang Wang Xiaoguang Liu Xiaoxiao Li FedML 30 8 0 01 Jun 2024
Cross-Training with Multi-View Knowledge Fusion for Heterogenous Federated Learning Zhuang Qi Lei Meng Weihao He Ruohan Zhang Yu Wang Xin Qi Xiangxu Meng FedML 28 4 0 30 May 2024
Analytic Federated Learning Huiping Zhuang Run He Kai Tong Di Fang Han Sun Haoran Li Tianyi Chen Ziqian Zeng FedML 22 3 0 25 May 2024
Exploring and Exploiting the Asymmetric Valley of Deep Neural Networks Xin-Chun Li Jinli Tang Bo Zhang Lan Li De-Chuan Zhan 30 2 0 21 May 2024
pFedAFM: Adaptive Feature Mixture for Batch-Level Personalization in Heterogeneous Federated Learning Liping Yi Han Yu Chao Ren Heng-Ming Zhang Gang Wang Xiaoguang Liu Xiaoxiao Li 23 2 0 27 Apr 2024
Towards Optimal Customized Architecture for Heterogeneous Federated Learning with Contrastive Cloud-Edge Model Decoupling Xingyan Chen Tian Du Mu Wang Tiancheng Gu Yu Zhao Gang Kou Changqiao Xu Dapeng Oliver Wu 29 2 0 04 Mar 2024
pFedMoE: Data-Level Personalization with Mixture of Experts for Model-Heterogeneous Personalized Federated Learning Liping Yi Han Yu Chao Ren Heng-Ming Zhang Gang Wang Xiaoguang Liu Xiaoxiao Li MoE 24 8 0 02 Feb 2024
Improving Local Training in Federated Learning via Temperature Scaling Kichang Lee Songkuk Kim Jeonggil Ko FedML 21 1 0 18 Jan 2024
FedFN: Feature Normalization for Alleviating Data Heterogeneity Problem in Federated Learning Seongyoon Kim Gihun Lee Jaehoon Oh Se-Young Yun 13 2 0 22 Nov 2023
FedHCA $^2$ : Towards Hetero-Client Federated Multi-Task Learning Yuxiang Lu Suizhi Huang Yuwen Yang Shalayiding Sirejiding Yue Ding Hongtao Lu FedML 34 3 0 22 Nov 2023
pFedES: Model Heterogeneous Personalized Federated Learning with Feature Extractor Sharing Liping Yi Han Yu Gang Wang Xiaoguang Liu 19 7 0 12 Nov 2023
Federated Learning with Manifold Regularization and Normalized Update Reaggregation Xuming An Li Shen Han Hu Yong Luo FedML 36 4 0 10 Nov 2023
pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning Liping Yi Han Yu Gang Wang Xiaoguang Liu Xiaoxiao Li 29 7 0 20 Oct 2023
Learning From Drift: Federated Learning on Non-IID Data via Drift Regularization Yeachan Kim Bonggun Shin FedML 14 0 0 13 Sep 2023
Efficient Federated Learning via Local Adaptive Amended Optimizer with Linear Speedup Yan Sun Li Shen Hao Sun Liang Ding Dacheng Tao FedML 19 16 0 30 Jul 2023
FedBug: A Bottom-Up Gradual Unfreezing Framework for Federated Learning Chia-Hsiang Kao Yu-Chiang Frank Wang FedML 9 1 0 19 Jul 2023
Towards Open Federated Learning Platforms: Survey and Vision from Technical and Legal Perspectives Moming Duan Qinbin Li Linshan Jiang Bingsheng He FedML 24 4 0 05 Jul 2023
Efficient Personalized Federated Learning via Sparse Model-Adaptation Daoyuan Chen Fandong Meng Dawei Gao Bolin Ding Yaliang Li FedML 96 47 0 04 May 2023
FedGH: Heterogeneous Federated Learning with Generalized Global Header Liping Yi Gang Wang Xiaoguang Liu Zhuan Shi Han Yu FedML 12 71 0 23 Mar 2023
DC-CCL: Device-Cloud Collaborative Controlled Learning for Large Vision Models Yucheng Ding Chaoyue Niu Fan Wu Shaojie Tang Chengfei Lyu Guihai Chen 10 6 0 18 Mar 2023
Making Batch Normalization Great in Federated Deep Learning Jike Zhong Hong-You Chen Wei-Lun Chao FedML 14 9 0 12 Mar 2023
Recent Advances on Federated Learning: A Systematic Survey Bingyan Liu Nuoyan Lv Yuanchun Guo Yawen Li FedML 55 78 0 03 Jan 2023
FedFA: Federated Learning with Feature Anchors to Align Features and Classifiers for Heterogeneous Data Tailin Zhou Jun Zhang Danny H. K. Tsang FedML 11 56 0 17 Nov 2022
FedClassAvg: Local Representation Learning for Personalized Federated Learning on Heterogeneous Neural Networks Jaehee Jang Heonseok Ha Dahuin Jung Sungroh Yoon FedML 16 39 0 25 Oct 2022
Wasserstein Barycenter-based Model Fusion and Linear Mode Connectivity of Neural Networks A. K. Akash Sixu Li Nicolas García Trillos 17 12 0 13 Oct 2022
TCT: Convexifying Federated Learning using Bootstrapped Neural Tangent Kernels Yaodong Yu Alexander Wei Sai Praneeth Karimireddy Yi-An Ma Michael I. Jordan FedML 6 30 0 13 Jul 2022
Mitigating Data Heterogeneity in Federated Learning with Data Augmentation Artur Back de Luca Guojun Zhang Xi Chen Yaoliang Yu FedML 15 29 0 20 Jun 2022
pFL-Bench: A Comprehensive Benchmark for Personalized Federated Learning Daoyuan Chen Dawei Gao Weirui Kuang Yaliang Li Bolin Ding FedML 25 63 0 08 Jun 2022
Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning Zhenheng Tang Yonggang Zhang S. Shi Xinfu He Bo Han X. Chu FedML 17 73 0 06 Jun 2022
FRAug: Tackling Federated Learning with Non-IID Features via Representation Augmentation Haokun Chen A. Frikha Denis Krompass Jindong Gu Volker Tresp OOD 19 24 0 30 May 2022
Federated Learning with Position-Aware Neurons Xin-Chun Li Yi-Chu Xu Shaoming Song Bingshuai Li Yinchuan Li Yunfeng Shao De-Chuan Zhan FedML 8 33 0 28 Mar 2022
Towards Model Agnostic Federated Learning Using Knowledge Distillation A. Afonin Sai Praneeth Karimireddy FedML 23 44 0 28 Oct 2021
Multi-Center Federated Learning: Clients Clustering for Better Personalization Guodong Long Ming Xie Tao Shen Tianyi Zhou Xianzhi Wang Jing Jiang Chengqi Zhang FedML 20 240 0 19 Aug 2021
Federated Learning on Non-IID Data: A Survey Hangyu Zhu Jinjin Xu Shiqing Liu Yaochu Jin OOD FedML 19 760 0 12 Jun 2021
Preservation of the Global Knowledge by Not-True Distillation in Federated Learning Gihun Lee Minchan Jeong Yongjin Shin Sangmin Bae Se-Young Yun FedML 20 112 0 06 Jun 2021
Distilling Critical Paths in Convolutional Neural Networks Fuxun Yu Zhuwei Qin Xiang Chen 26 21 0 28 Oct 2018
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 948 20,471 0 17 Apr 2017
Do semantic parts emerge in Convolutional Neural Networks? Abel Gonzalez-Garcia Davide Modolo V. Ferrari 150 113 0 13 Jul 2016