Loop Improvement: An Efficient Approach for Extracting Shared Features
from Heterogeneous Data without Central Server

Loop Improvement: An Efficient Approach for Extracting Shared Features from Heterogeneous Data without Central Server

21 March 2024

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Papers citing "Loop Improvement: An Efficient Approach for Extracting Shared Features from Heterogeneous Data without Central Server"

16 / 16 papers shown

Title
FedALA: Adaptive Local Aggregation for Personalized Federated Learning Jianqing Zhang Yang Hua Hao Wang Tao Song Zhengui Xue Ruhui Ma Haibing Guan FedML 70 229 0 02 Dec 2022
Where to Begin? On the Impact of Pre-Training and Initialization in Federated Learning John Nguyen Jianyu Wang Kshitiz Malik Maziar Sanjabi Michael G. Rabbat FedML AI4CE 81 73 0 14 Oct 2022
A Multi-modal Fusion Framework Based on Multi-task Correlation Learning for Cancer Prognosis Prediction Kaiwen Tan Weixian Huang Xiaofeng Liu Jinlong Hu Shoubin Dong 32 42 0 22 Jan 2022
FedLab: A Flexible Federated Learning Framework Dun Zeng Siqi Liang Xiangjing Hu Hui Wang Zenglin Xu FedML 66 114 0 24 Jul 2021
Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning Liangqiong Qu Yuyin Zhou Paul Pu Liang Yingda Xia Feifei Wang Ehsan Adeli L. Fei-Fei D. Rubin FedML AI4CE 67 183 0 10 Jun 2021
No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data Mi Luo Fei Chen Dapeng Hu Yifan Zhang Jian Liang Jiashi Feng FedML 83 342 0 09 Jun 2021
CoAtNet: Marrying Convolution and Attention for All Data Sizes Zihang Dai Hanxiao Liu Quoc V. Le Mingxing Tan ViT 123 1,208 0 09 Jun 2021
Towards Personalized Federated Learning A. Tan Han Yu Li-zhen Cui Qiang Yang FedML AI4CE 327 873 0 01 Mar 2021
PFL-MoE: Personalized Federated Learning Based on Mixture of Experts Binbin Guo Yuan Mei Danyang Xiao Weigang Wu Ye Yin Hongli Chang MoE 90 22 0 31 Dec 2020
Federated Continual Learning with Weighted Inter-client Transfer Jaehong Yoon Wonyoung Jeong Giwoong Lee Eunho Yang Sung Ju Hwang FedML 95 209 0 06 Mar 2020
Think Locally, Act Globally: Federated Learning with Local and Global Representations Paul Pu Liang Terrance Liu Liu Ziyin Nicholas B. Allen Randy P. Auerbach David Brent Ruslan Salakhutdinov Louis-Philippe Morency FedML 117 563 0 06 Jan 2020
Federated Learning with Personalization Layers Manoj Ghuhan Arivazhagan V. Aggarwal Aaditya Kumar Singh Sunav Choudhary FedML 94 839 0 02 Dec 2019
A Downsampled Variant of ImageNet as an Alternative to the CIFAR datasets P. Chrabaszcz I. Loshchilov Frank Hutter SSeg OOD 163 649 0 27 Jul 2017
A Survey on Multi-Task Learning Yu Zhang Qiang Yang AIMat 605 2,235 0 25 Jul 2017
Bag of Tricks for Efficient Text Classification Armand Joulin Edouard Grave Piotr Bojanowski Tomas Mikolov VLM 177 4,630 0 06 Jul 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 406 17,559 0 17 Feb 2016

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