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SetConv: A New Approach for Learning from Imbalanced Data

SetConv: A New Approach for Learning from Imbalanced Data

3 April 2021
Y. Gao
Yifan Li
Yu Lin
Charu C. Aggarwal
Latifur Khan
ArXiv (abs)PDFHTML

Papers citing "SetConv: A New Approach for Learning from Imbalanced Data"

3 / 3 papers shown
Title
APAM: Adaptive Pre-training and Adaptive Meta Learning in Language Model
  for Noisy Labels and Long-tailed Learning
APAM: Adaptive Pre-training and Adaptive Meta Learning in Language Model for Noisy Labels and Long-tailed Learning
Sunyi Chi
B. Dong
Yiming Xu
Zhenyu Shi
Zheng Du
NoLa
99
3
0
06 Feb 2023
A Survey of Methods for Addressing Class Imbalance in Deep-Learning
  Based Natural Language Processing
A Survey of Methods for Addressing Class Imbalance in Deep-Learning Based Natural Language Processing
Sophie Henning
William H. Beluch
Alexander Fraser
Annemarie Friedrich
39
22
0
10 Oct 2022
Distance-wise Prototypical Graph Neural Network in Node Imbalance
  Classification
Distance-wise Prototypical Graph Neural Network in Node Imbalance Classification
Yu Wang
Siegfried Mercelis
Hanyu Wang
111
22
0
22 Oct 2021
1