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Rethinking Soft Label in Label Distribution Learning Perspective

Rethinking Soft Label in Label Distribution Learning Perspective

31 January 2023
Seungbum Hong
Jihun Yoon
Bogyu Park
Min-Kook Choi
ArXivPDFHTML

Papers citing "Rethinking Soft Label in Label Distribution Learning Perspective"

17 / 17 papers shown
Title
Decompositional Generation Process for Instance-Dependent Partial Label
  Learning
Decompositional Generation Process for Instance-Dependent Partial Label Learning
Congyu Qiao
Ning Xu
Xin Geng
155
82
0
08 Apr 2022
Is Label Smoothing Truly Incompatible with Knowledge Distillation: An
  Empirical Study
Is Label Smoothing Truly Incompatible with Knowledge Distillation: An Empirical Study
Zhiqiang Shen
Zechun Liu
Dejia Xu
Zitian Chen
Kwang-Ting Cheng
Marios Savvides
43
76
0
01 Apr 2021
Rethinking Soft Labels for Knowledge Distillation: A Bias-Variance
  Tradeoff Perspective
Rethinking Soft Labels for Knowledge Distillation: A Bias-Variance Tradeoff Perspective
Helong Zhou
Liangchen Song
Jiajie Chen
Ye Zhou
Guoli Wang
Junsong Yuan
Qian Zhang
67
174
0
01 Feb 2021
Improving model calibration with accuracy versus uncertainty
  optimization
Improving model calibration with accuracy versus uncertainty optimization
R. Krishnan
Omesh Tickoo
UQCV
230
163
0
14 Dec 2020
MEAL V2: Boosting Vanilla ResNet-50 to 80%+ Top-1 Accuracy on ImageNet
  without Tricks
MEAL V2: Boosting Vanilla ResNet-50 to 80%+ Top-1 Accuracy on ImageNet without Tricks
Zhiqiang Shen
Marios Savvides
59
63
0
17 Sep 2020
Knowledge Distillation Meets Self-Supervision
Knowledge Distillation Meets Self-Supervision
Guodong Xu
Ziwei Liu
Xiaoxiao Li
Chen Change Loy
FedML
69
285
0
12 Jun 2020
Peer Collaborative Learning for Online Knowledge Distillation
Peer Collaborative Learning for Online Knowledge Distillation
Guile Wu
S. Gong
FedML
39
129
0
07 Jun 2020
Contrastive Representation Distillation
Contrastive Representation Distillation
Yonglong Tian
Dilip Krishnan
Phillip Isola
144
1,048
0
23 Oct 2019
When Does Label Smoothing Help?
When Does Label Smoothing Help?
Rafael Müller
Simon Kornblith
Geoffrey E. Hinton
UQCV
191
1,945
0
06 Jun 2019
CutMix: Regularization Strategy to Train Strong Classifiers with
  Localizable Features
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
Sangdoo Yun
Dongyoon Han
Seong Joon Oh
Sanghyuk Chun
Junsuk Choe
Y. Yoo
OOD
609
4,777
0
13 May 2019
mixup: Beyond Empirical Risk Minimization
mixup: Beyond Empirical Risk Minimization
Hongyi Zhang
Moustapha Cissé
Yann N. Dauphin
David Lopez-Paz
NoLa
273
9,760
0
25 Oct 2017
Deep Layer Aggregation
Deep Layer Aggregation
Feng Yu
Dequan Wang
Evan Shelhamer
Trevor Darrell
AI4CE
FAtt
144
1,328
0
20 Jul 2017
Paying More Attention to Attention: Improving the Performance of
  Convolutional Neural Networks via Attention Transfer
Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer
Sergey Zagoruyko
N. Komodakis
118
2,579
0
12 Dec 2016
Aggregated Residual Transformations for Deep Neural Networks
Aggregated Residual Transformations for Deep Neural Networks
Saining Xie
Ross B. Girshick
Piotr Dollár
Zhuowen Tu
Kaiming He
509
10,322
0
16 Nov 2016
Densely Connected Convolutional Networks
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
Laurens van der Maaten
Kilian Q. Weinberger
PINN
3DV
766
36,794
0
25 Aug 2016
Rethinking the Inception Architecture for Computer Vision
Rethinking the Inception Architecture for Computer Vision
Christian Szegedy
Vincent Vanhoucke
Sergey Ioffe
Jonathon Shlens
Z. Wojna
3DV
BDL
872
27,350
0
02 Dec 2015
FitNets: Hints for Thin Deep Nets
FitNets: Hints for Thin Deep Nets
Adriana Romero
Nicolas Ballas
Samira Ebrahimi Kahou
Antoine Chassang
C. Gatta
Yoshua Bengio
FedML
298
3,883
0
19 Dec 2014
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