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2007.02235
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Unbiased Risk Estimators Can Mislead: A Case Study of Learning with Complementary Labels
5 July 2020
Yu-Ting Chou
Gang Niu
Hsuan-Tien Lin
Masashi Sugiyama
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Papers citing
"Unbiased Risk Estimators Can Mislead: A Case Study of Learning with Complementary Labels"
25 / 25 papers shown
Title
Learning with Multiple Complementary Labels
Lei Feng
Takuo Kaneko
Bo Han
Gang Niu
Bo An
Masashi Sugiyama
75
98
0
30 Dec 2019
Mitigating Overfitting in Supervised Classification from Two Unlabeled Datasets: A Consistent Risk Correction Approach
Nan Lu
Tianyi Zhang
Gang Niu
Masashi Sugiyama
54
55
0
20 Oct 2019
NLNL: Negative Learning for Noisy Labels
Youngdong Kim
Junho Yim
Juseung Yun
Junmo Kim
NoLa
52
277
0
19 Aug 2019
Are Anchor Points Really Indispensable in Label-Noise Learning?
Xiaobo Xia
Tongliang Liu
N. Wang
Bo Han
Chen Gong
Gang Niu
Masashi Sugiyama
NoLa
73
381
0
01 Jun 2019
Generative-Discriminative Complementary Learning
Yanwu Xu
Biwei Huang
Junxiang Chen
Tongliang Liu
Kun Zhang
Kayhan Batmanghelich
GAN
40
38
0
02 Apr 2019
Uniform convergence may be unable to explain generalization in deep learning
Vaishnavh Nagarajan
J. Zico Kolter
MoMe
AI4CE
81
315
0
13 Feb 2019
Online Multiclass Classification Based on Prediction Margin for Partial Feedback
Takuo Kaneko
Issei Sato
Masashi Sugiyama
29
12
0
04 Feb 2019
How does Disagreement Help Generalization against Label Corruption?
Xingrui Yu
Bo Han
Jiangchao Yao
Gang Niu
Ivor W. Tsang
Masashi Sugiyama
NoLa
76
787
0
14 Jan 2019
Complementary-Label Learning for Arbitrary Losses and Models
Takashi Ishida
Gang Niu
A. Menon
Masashi Sugiyama
VLM
56
113
0
10 Oct 2018
Classification from Positive, Unlabeled and Biased Negative Data
Yu-Guan Hsieh
Gang Niu
Masashi Sugiyama
55
80
0
01 Oct 2018
On the Minimal Supervision for Training Any Binary Classifier from Only Unlabeled Data
Nan Lu
Gang Niu
A. Menon
Masashi Sugiyama
MQ
73
87
0
31 Aug 2018
Masking: A New Perspective of Noisy Supervision
Bo Han
Jiangchao Yao
Gang Niu
Mingyuan Zhou
Ivor Tsang
Ya Zhang
Masashi Sugiyama
NoLa
73
255
0
21 May 2018
Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels
Bo Han
Quanming Yao
Xingrui Yu
Gang Niu
Miao Xu
Weihua Hu
Ivor Tsang
Masashi Sugiyama
NoLa
118
2,078
0
18 Apr 2018
Classification from Pairwise Similarity and Unlabeled Data
Han Bao
Gang Niu
Masashi Sugiyama
223
88
0
12 Feb 2018
Learning with Biased Complementary Labels
Xiyu Yu
Tongliang Liu
Biwei Huang
Dacheng Tao
59
198
0
27 Nov 2017
Binary Classification from Positive-Confidence Data
Takashi Ishida
Gang Niu
Masashi Sugiyama
57
57
0
19 Oct 2017
Learning from Complementary Labels
Takashi Ishida
Gang Niu
Weihua Hu
Masashi Sugiyama
53
168
0
22 May 2017
Semi-Supervised AUC Optimization based on Positive-Unlabeled Learning
Tomoya Sakai
Gang Niu
Masashi Sugiyama
56
61
0
04 May 2017
Positive-Unlabeled Learning with Non-Negative Risk Estimator
Ryuichi Kiryo
Gang Niu
M. C. D. Plessis
Masashi Sugiyama
71
478
0
02 Mar 2017
Understanding deep learning requires rethinking generalization
Chiyuan Zhang
Samy Bengio
Moritz Hardt
Benjamin Recht
Oriol Vinyals
HAI
345
4,636
0
10 Nov 2016
Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach
Giorgio Patrini
A. Rozza
A. Menon
Richard Nock
Zhuang Li
NoLa
113
1,458
0
13 Sep 2016
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
Laurens van der Maaten
Kilian Q. Weinberger
PINN
3DV
775
36,861
0
25 Aug 2016
Theoretical Comparisons of Positive-Unlabeled Learning against Positive-Negative Learning
Gang Niu
M. C. D. Plessis
Tomoya Sakai
Yao Ma
Masashi Sugiyama
69
128
0
10 Mar 2016
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
194,322
0
10 Dec 2015
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
2.0K
150,260
0
22 Dec 2014
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