A Survey on Class Imbalance in Federated Learning

21 March 2023

Papers citing "A Survey on Class Imbalance in Federated Learning"

8 / 8 papers shown

Title
Drift-Aware Federated Learning: A Causal Perspective Yunjie Fang Sheng Wu Tao Yang X. Wu Bo Hu FedML 50 0 0 13 Mar 2025
Federated Learning with MMD-based Early Stopping for Adaptive GNSS Interference Classification Nishant S. Gaikwad Lucas Heublein N. Raichur Tobias Feigl Christopher Mutschler Felix Ott 48 5 0 31 Dec 2024
Partial Knowledge Distillation for Alleviating the Inherent Inter-Class Discrepancy in Federated Learning Xiaoyu Gan Xizi Chen Jingyang Zhu Xiaomeng Wang Jingbo Jiang Chi-Ying Tsui FedML 82 0 0 23 Nov 2024
On Homomorphic Encryption Based Strategies for Class Imbalance in Federated Learning Arpit Guleria J. Harshan Ranjitha Prasad B. N. Bharath FedML 16 0 0 28 Oct 2024
FedDistill: Global Model Distillation for Local Model De-Biasing in Non-IID Federated Learning Changlin Song Divya Saxena Jiannong Cao Yuqing Zhao FedML 25 3 0 14 Apr 2024
Not all Minorities are Equal: Empty-Class-Aware Distillation for Heterogeneous Federated Learning Kuangpu Guo Yuhe Ding Jian Liang R. He Zilei Wang Tieniu Tan FedML 20 1 0 04 Jan 2024
Dubhe: Towards Data Unbiasedness with Homomorphic Encryption in Federated Learning Client Selection Shulai Zhang Zirui Li Quan Chen Wenli Zheng Jingwen Leng M. Guo FedML 54 32 0 08 Sep 2021
SMOTE: Synthetic Minority Over-sampling Technique Nitesh V. Chawla Kevin W. Bowyer Lawrence Hall W. Kegelmeyer AI4TS 160 25,214 0 09 Jun 2011