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Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning
Computer Vision and Pattern Recognition (CVPR), 2021
10 June 2021
Liangqiong Qu
Yuyin Zhou
Paul Pu Liang
Yingda Xia
Feifei Wang
Ehsan Adeli
L. Fei-Fei
D. Rubin
FedML
AI4CE
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Papers citing
"Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning"
50 / 101 papers shown
ARIA: On the Interaction Between Architectures, Initialization and Aggregation Methods for Federated Visual Classification
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223
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0
24 Nov 2023
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Wan-Yi Lin
Devin Willmott
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Zhenzhen Li
Madan Ravi Ganesh
FedML
205
5
0
14 Nov 2023
A Federated Data Fusion-Based Prognostic Model for Applications with Multi-Stream Incomplete Signals
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Madi Arabi
Xiaolei Fang
FedML
187
3
0
13 Nov 2023
Unlocking the Potential of Prompt-Tuning in Bridging Generalized and Personalized Federated Learning
Computer Vision and Pattern Recognition (CVPR), 2023
Wenlong Deng
Christos Thrampoulidis
Xiaoxiao Li
632
20
0
27 Oct 2023
Handling Data Heterogeneity via Architectural Design for Federated Visual Recognition
Neural Information Processing Systems (NeurIPS), 2023
Sara Pieri
Jose Renato Restom
Samuel Horvath
Hisham Cholakkal
FedML
167
9
0
23 Oct 2023
Tackling Heterogeneity in Medical Federated learning via Vision Transformers
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Yiqing Shen
Yangming Ou
N. Sijtsema
P. V. Ooijen
MedIm
FedML
263
0
0
13 Oct 2023
FedSym: Unleashing the Power of Entropy for Benchmarking the Algorithms for Federated Learning
BigData Congress [Services Society] (BSS), 2023
Ensiye Kiyamousavi
Boris Kraychev
Ivan Koychev
FedML
187
0
0
11 Oct 2023
Federated Self-Supervised Learning of Monocular Depth Estimators for Autonomous Vehicles
Elton F. S. Soares
Carlos Alberto V. Campos
MDE
FedML
190
3
0
07 Oct 2023
FedConv: Enhancing Convolutional Neural Networks for Handling Data Heterogeneity in Federated Learning
Peiran Xu
Zeyu Wang
Jieru Mei
Liangqiong Qu
Yaoyao Liu
Cihang Xie
Yuyin Zhou
FedML
161
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06 Oct 2023
Chained-DP: Can We Recycle Privacy Budget?
International Workshop on Quality of Service (IWQoS), 2023
Jingyi Li
Guangjing Huang
Liekang Zeng
Lin Chen
Xu Chen
FedML
281
0
0
12 Sep 2023
Jointly Exploring Client Drift and Catastrophic Forgetting in Dynamic Learning
Scientific Reports (Sci Rep), 2023
Niklas Babendererde
Moritz Fuchs
Camila González
Yuri Tolkach
Anirban Mukhopadhyay
OOD
FedML
211
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01 Sep 2023
Efficient Model Personalization in Federated Learning via Client-Specific Prompt Generation
IEEE International Conference on Computer Vision (ICCV), 2023
Fu-En Yang
Chien-Yi Wang
Yu-Chiang Frank Wang
VLM
FedML
282
102
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29 Aug 2023
Federated Learning for Computer Vision
Yassine Himeur
Iraklis Varlamis
Hamza Kheddar
Abbes Amira
Shadi Atalla
Yashbir Singh
F. Bensaali
Shadi Atalla
FedML
226
47
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24 Aug 2023
Federated Learning in Big Model Era: Domain-Specific Multimodal Large Models
Zengxiang Li
Zhaoxiang Hou
Hui Liu
Ying Wang
Tongzhi Li
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Chao Shi
Che-Sheng Yang
Weishan Zhang
Zelei Liu
Liang Xu
FedML
159
3
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22 Aug 2023
FedPerfix: Towards Partial Model Personalization of Vision Transformers in Federated Learning
IEEE International Conference on Computer Vision (ICCV), 2023
Guangyu Sun
Matías Mendieta
Jun Luo
Shandong Wu
Chong Chen
214
26
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17 Aug 2023
The Prospect of Enhancing Large-Scale Heterogeneous Federated Learning with Transformers
Yulan Gao
Zhaoxiang Hou
Che-Sheng Yang
Zengxiang Li
Han Yu
FedML
123
4
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07 Aug 2023
Cross-Silo Prototypical Calibration for Federated Learning with Non-IID Data
ACM Multimedia (ACM MM), 2023
Zhuang Qi
Lei Meng
Zitan Chen
Han Hu
Hui Lin
Xiangxu Meng
FedML
206
43
0
07 Aug 2023
Heterogeneous Federated Learning: State-of-the-art and Research Challenges
ACM Computing Surveys (ACM Comput. Surv.), 2023
Mang Ye
Xiuwen Fang
Bo Du
PongChi Yuen
Dacheng Tao
FedML
AAML
472
471
0
20 Jul 2023
A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning
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Zhenyi Wang
Enneng Yang
Li Shen
Heng-Chiao Huang
KELM
MU
278
88
0
16 Jul 2023
FedYolo: Augmenting Federated Learning with Pretrained Transformers
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Mingchen Li
Xiangyu Chang
Jiasi Chen
Amit K. Roy-Chowdhury
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Samet Oymak
FedML
209
10
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10 Jul 2023
SelfFed: Self-Supervised Federated Learning for Data Heterogeneity and Label Scarcity in Medical Images
Expert systems with applications (ESWA), 2023
Sunder Ali Khowaja
Kapal Dev
Syed Muhammad Anwar
M. Linguraru
FedML
144
3
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04 Jul 2023
Resource Aware Clustering for Tackling the Heterogeneity of Participants in Federated Learning
Rahul Mishra
Hari Prabhat Gupta
Garvit Banga
FedML
139
7
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07 Jun 2023
Byzantine-Robust Clustered Federated Learning
Zhixu Tao
Kun Yang
Sanjeev R. Kulkarni
OOD
FedML
126
2
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01 Jun 2023
FedBEVT: Federated Learning Bird's Eye View Perception Transformer in Road Traffic Systems
IEEE Transactions on Intelligent Vehicles (TIV), 2023
Rui Song
Runsheng Xu
Andreas Festag
Jiaqi Ma
Alois Knoll
FedML
240
37
0
04 Apr 2023
Fair Federated Medical Image Segmentation via Client Contribution Estimation
Computer Vision and Pattern Recognition (CVPR), 2023
Meirui Jiang
H. Roth
Wenqi Li
Dong Yang
Can Zhao
V. Nath
Daguang Xu
Qianming Dou
Ziyue Xu
FedML
187
77
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29 Mar 2023
An Evaluation of Non-Contrastive Self-Supervised Learning for Federated Medical Image Analysis
Soumitri Chattopadhyay
Soham Ganguly
Sreejit Chaudhury
Sayan Nag
S. Chattopadhyay
154
0
0
09 Mar 2023
Memory-adaptive Depth-wise Heterogeneous Federated Learning
Kai Zhang
Yutong Dai
Hongyi Wang
Eric P. Xing
Hang Zhang
Lichao Sun
FedML
203
10
0
08 Mar 2023
On the Efficacy of Differentially Private Few-shot Image Classification
Marlon Tobaben
Aliaksandra Shysheya
J. Bronskill
Andrew Paverd
Shruti Tople
Santiago Zanella Béguelin
Richard Turner
Antti Honkela
412
16
0
02 Feb 2023
No One Left Behind: Real-World Federated Class-Incremental Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
Jiahua Dong
Hongliu Li
Yang Cong
Gan Sun
Yulun Zhang
Dengxin Dai
FedML
CLL
395
72
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02 Feb 2023
Contrast with Major Classifier Vectors for Federated Medical Relation Extraction with Heterogeneous Label Distribution
Chunhui Du
Hao He
Yaohui Jin
123
2
0
13 Jan 2023
Why Batch Normalization Damage Federated Learning on Non-IID Data?
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023
Yanmeng Wang
Qingjiang Shi
Tsung-Hui Chang
FedML
338
53
0
08 Jan 2023
Single-round Self-supervised Distributed Learning using Vision Transformer
Sangjoon Park
Ik-jae Lee
Jun Won Kim
Jong Chul Ye
FedML
MedIm
323
1
0
05 Jan 2023
When Federated Learning Meets Pre-trained Language Models' Parameter-Efficient Tuning Methods
Annual Meeting of the Association for Computational Linguistics (ACL), 2022
Zhuo Zhang
Yuanhang Yang
Yong Dai
Zhuang Li
Zenglin Xu
FedML
441
114
0
20 Dec 2022
Robust Split Federated Learning for U-shaped Medical Image Networks
Ziyuan Yang
Yingyu Chen
Huijie Huangfu
Maosong Ran
Hui Wang
Xiaoxiao Li
Yi Zhang
OOD
FedML
176
14
0
13 Dec 2022
Federated Learning for Inference at Anytime and Anywhere
Zicheng Liu
Da Li
Javier Fernandez-Marques
Stefanos Laskaridis
Yan Gao
Łukasz Dudziak
Stan Z. Li
S. Hu
Timothy M. Hospedales
FedML
167
6
0
08 Dec 2022
Federated Learning Attacks and Defenses: A Survey
Yao Chen
Yijie Gui
Hong Lin
Wensheng Gan
Yongdong Wu
FedML
200
43
0
27 Nov 2022
Explainable, Domain-Adaptive, and Federated Artificial Intelligence in Medicine
IEEE/CAA Journal of Automatica Sinica (JCAS), 2022
Ahmad Chaddad
Qizong Lu
Jiali Li
Y. Katib
R. Kateb
C. Tanougast
Ahmed Bouridane
Ahmed Abdulkadir
OOD
252
56
0
17 Nov 2022
FedTune: A Deep Dive into Efficient Federated Fine-Tuning with Pre-trained Transformers
Jinyu Chen
Wenchao Xu
Song Guo
Junxiao Wang
Jie Zhang
Yining Qi
FedML
202
45
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15 Nov 2022
FedTP: Federated Learning by Transformer Personalization
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Hongxia Li
Zhongyi Cai
Jingya Wang
Jiangnan Tang
Weiping Ding
Chin-Teng Lin
Ye-ling Shi
FedML
323
111
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03 Nov 2022
When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture
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Dongxian Wu
Yifei Wang
Yiwen Guo
Yisen Wang
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272
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Federated Learning from Pre-Trained Models: A Contrastive Learning Approach
Neural Information Processing Systems (NeurIPS), 2022
Yue Tan
Guodong Long
Jie Ma
Lu Liu
Tianyi Zhou
Jing Jiang
FedML
316
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21 Sep 2022
Exploring Semantic Attributes from A Foundation Model for Federated Learning of Disjoint Label Spaces
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Chenyang Si
Guile Wu
S. Gong
FedML
314
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29 Aug 2022
PromptFL: Let Federated Participants Cooperatively Learn Prompts Instead of Models -- Federated Learning in Age of Foundation Model
IEEE Transactions on Mobile Computing (IEEE TMC), 2022
Tao Guo
Song Guo
Junxiao Wang
Wenchao Xu
FedML
VLM
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200
190
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Reducing Training Time in Cross-Silo Federated Learning using Multigraph Topology
IEEE International Conference on Computer Vision (ICCV), 2022
Tuong Khanh Long Do
Binh X. Nguyen
Vuong Pham
Toan V. Tran
Erman Tjiputra
Quang-Dieu Tran
A. Nguyen
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391
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Jihong Park
Praneeth Vepakomma
Ramesh Raskar
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Seong-Lyun Kim
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169
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01 Jul 2022
On the Importance and Applicability of Pre-Training for Federated Learning
International Conference on Learning Representations (ICLR), 2022
Hong-You Chen
Cheng-Hao Tu
Zi-hua Li
Hang Shen
Wei-Lun Chao
FedML
355
104
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23 Jun 2022
Federated Adversarial Training with Transformers
Ahmed Aldahdooh
W. Hamidouche
Olivier Déforges
FedML
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230
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Can Foundation Models Help Us Achieve Perfect Secrecy?
Simran Arora
Christopher Ré
FedML
251
12
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Label-Efficient Self-Supervised Federated Learning for Tackling Data Heterogeneity in Medical Imaging
IEEE Transactions on Medical Imaging (IEEE TMI), 2022
Rui Yan
Liangqiong Qu
Qingyue Wei
Shih-Cheng Huang
Liyue Shen
D. Rubin
Lei Xing
Yuyin Zhou
FedML
277
148
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SplitAVG: A heterogeneity-aware federated deep learning method for medical imaging
Miao Zhang
Liangqiong Qu
Praveer Singh
Jayashree Kalpathy-Cramer
D. Rubin
OOD
FedML
464
71
0
06 Jul 2021
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