Addressing Class Variable Imbalance in Federated Semi-supervised Learning

21 March 2023

Papers citing "Addressing Class Variable Imbalance in Federated Semi-supervised Learning"

8 / 8 papers shown

Title
Self-Training: A Survey Massih-Reza Amini Vasilii Feofanov Loïc Pauletto Lies Hadjadj Emilie Devijver Yury Maximov SSL 101 105 0 24 Feb 2022
CReST: A Class-Rebalancing Self-Training Framework for Imbalanced Semi-Supervised Learning Chen Wei Kihyuk Sohn Clayton Mellina Alan Yuille Fan Yang CLL 100 265 0 18 Feb 2021
Federated learning with class imbalance reduction Miao Yang Akitanoshou Wong Hongbin Zhu Haifeng Wang H. Qian FedML 61 125 0 23 Nov 2020
Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning Wonyong Jeong Jaehong Yoon Eunho Yang Sung Ju Hwang FedML 56 221 0 22 Jun 2020
Rethinking the Value of Labels for Improving Class-Imbalanced Learning Yuzhe Yang Zhi Xu SSL 126 413 0 13 Jun 2020
Equalization Loss for Long-Tailed Object Recognition Jingru Tan Changbao Wang Buyu Li Quanquan Li Wanli Ouyang Changqing Yin Junjie Yan 318 466 0 11 Mar 2020
Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks Haebeom Lee Hayeon Lee Donghyun Na Saehoon Kim Minseop Park Eunho Yang Sung Ju Hwang BDL OODD 73 107 0 30 May 2019
Caffe: Convolutional Architecture for Fast Feature Embedding Yangqing Jia Evan Shelhamer Jeff Donahue Sergey Karayev Jonathan Long Ross B. Girshick S. Guadarrama Trevor Darrell VLM BDL 3DV 280 14,713 0 20 Jun 2014