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kaidic
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LDAM-DRW
[NeurIPS 2019] Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss
https://arxiv.org/pdf/1906.07413.pdf
MIT License
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Using gereral Resnet causes the loss to become ’nan‘
#20
zh-jp
closed
7 months ago
1
CE+DRW and CE+CB
#19
xiaohua-chen
opened
2 years ago
0
Update utils.py
#18
bhavinjawade
closed
2 years ago
0
Focal loss would lead to nan?
#17
liming-ai
closed
3 years ago
1
the learning rate in log_train times 0.1
#16
yibuxulong
opened
3 years ago
0
VS Loss added
#15
orparask
closed
3 years ago
1
Can not achieve similar results For Tiny ImageNet
#14
MapleLeafKiller
opened
3 years ago
0
About the LDAM Loss
#13
sakumashirayuki
opened
3 years ago
4
more details about your paper
#12
zj-jayzhang
opened
4 years ago
0
AttributeError: 'IMBALANCECIFAR10' object has no attribute 'data'
#11
xinfu607
opened
4 years ago
1
how bout both training set and test set are same imbalanced?
#10
SeunghyunSEO
opened
4 years ago
2
Is there any pretrain model?
#9
BIGROOKIE24
opened
4 years ago
0
Any Experiments on Face Recognition?
#8
terrencew
opened
4 years ago
0
Points for sampler
#7
halbielee
opened
4 years ago
5
Wrong implementation of focal loss
#6
AlanChou
closed
4 years ago
2
Codes for iNaturalist experiments?
#5
abdullahjamal
opened
5 years ago
1
ERM Baseline
#4
hbsz123
opened
5 years ago
1
DRW actually use Class-Balance Weight, instead of Inverse of Frequency
#3
chuong98
closed
5 years ago
1
Questions about the hyper-parameters for LDAM loss
#2
hyungwonchoi
closed
5 years ago
3
Whats ETA on code release?
#1
fahad92virgo
closed
5 years ago
1