Local or Global: Selective Knowledge Assimilation for Federated Learning with Limited Labels

17 July 2023

Papers citing "Local or Global: Selective Knowledge Assimilation for Federated Learning with Limited Labels"

5 / 5 papers shown

Title
MedMNIST v2 -- A large-scale lightweight benchmark for 2D and 3D biomedical image classification Jiancheng Yang Rui Shi D. Wei Zequan Liu Lin Zhao B. Ke Hanspeter Pfister Bingbing Ni VLM 168 647 0 27 Oct 2021
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling Bowen Zhang Yidong Wang Wenxin Hou Hao Wu Jindong Wang Manabu Okumura T. Shinozaki AAML 226 862 0 15 Oct 2021
SSFL: Tackling Label Deficiency in Federated Learning via Personalized Self-Supervision Chaoyang He Zhengyu Yang Erum Mushtaq Sunwoo Lee Mahdi Soltanolkotabi A. Avestimehr FedML 95 36 0 06 Oct 2021
A Field Guide to Federated Optimization Jianyu Wang Zachary B. Charles Zheng Xu Gauri Joshi H. B. McMahan ... Mi Zhang Tong Zhang Chunxiang Zheng Chen Zhu Wennan Zhu FedML 178 411 0 14 Jul 2021
GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs Binghui Wang Ang Li H. Li Yiran Chen 82 115 0 08 Dec 2020