ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1906.00189
  4. Cited By
Are Anchor Points Really Indispensable in Label-Noise Learning?

Are Anchor Points Really Indispensable in Label-Noise Learning?

1 June 2019
Xiaobo Xia
Tongliang Liu
N. Wang
Bo Han
Chen Gong
Gang Niu
Masashi Sugiyama
    NoLa
ArXivPDFHTML

Papers citing "Are Anchor Points Really Indispensable in Label-Noise Learning?"

30 / 80 papers shown
Title
SENT: Sentence-level Distant Relation Extraction via Negative Training
SENT: Sentence-level Distant Relation Extraction via Negative Training
Ruotian Ma
Tao Gui
Linyang Li
Qi Zhang
Yaqian Zhou
Xuanjing Huang
22
28
0
22 Jun 2021
Towards Understanding Deep Learning from Noisy Labels with Small-Loss
  Criterion
Towards Understanding Deep Learning from Noisy Labels with Small-Loss Criterion
Xian-Jin Gui
Wei Wang
Zhang-Hao Tian
NoLa
33
44
0
17 Jun 2021
Leveraged Weighted Loss for Partial Label Learning
Leveraged Weighted Loss for Partial Label Learning
Hongwei Wen
Jingyi Cui
H. Hang
Jiabin Liu
Yisen Wang
Zhouchen Lin
16
95
0
10 Jun 2021
CCMN: A General Framework for Learning with Class-Conditional
  Multi-Label Noise
CCMN: A General Framework for Learning with Class-Conditional Multi-Label Noise
Ming-Kun Xie
Sheng-Jun Huang
NoLa
24
25
0
16 May 2021
Generalized Jensen-Shannon Divergence Loss for Learning with Noisy
  Labels
Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels
Erik Englesson
Hossein Azizpour
NoLa
34
104
0
10 May 2021
Removing Adversarial Noise in Class Activation Feature Space
Removing Adversarial Noise in Class Activation Feature Space
Dawei Zhou
N. Wang
Chunlei Peng
Xinbo Gao
Xiaoyu Wang
Jun Yu
Tongliang Liu
AAML
30
28
0
19 Apr 2021
Learning from Noisy Labels via Dynamic Loss Thresholding
Learning from Noisy Labels via Dynamic Loss Thresholding
Hao Yang
Youzhi Jin
Zi-Hua Li
Deng-Bao Wang
Lei Miao
Xin Geng
Min-Ling Zhang
NoLa
AI4CE
32
6
0
01 Apr 2021
From Synthetic to Real: Unsupervised Domain Adaptation for Animal Pose
  Estimation
From Synthetic to Real: Unsupervised Domain Adaptation for Animal Pose Estimation
Chen Li
G. Lee
OOD
17
81
0
27 Mar 2021
Learning from Similarity-Confidence Data
Learning from Similarity-Confidence Data
Yuzhou Cao
Lei Feng
Yitian Xu
Bo An
Gang Niu
Masashi Sugiyama
27
17
0
13 Feb 2021
Clusterability as an Alternative to Anchor Points When Learning with
  Noisy Labels
Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels
Zhaowei Zhu
Yiwen Song
Yang Liu
NoLa
21
91
0
10 Feb 2021
Provably End-to-end Label-Noise Learning without Anchor Points
Provably End-to-end Label-Noise Learning without Anchor Points
Xuefeng Li
Tongliang Liu
Bo Han
Gang Niu
Masashi Sugiyama
NoLa
133
121
0
04 Feb 2021
Analysing the Noise Model Error for Realistic Noisy Label Data
Analysing the Noise Model Error for Realistic Noisy Label Data
Michael A. Hedderich
D. Zhu
Dietrich Klakow
NoLa
31
19
0
24 Jan 2021
Dual-Refinement: Joint Label and Feature Refinement for Unsupervised
  Domain Adaptive Person Re-Identification
Dual-Refinement: Joint Label and Feature Refinement for Unsupervised Domain Adaptive Person Re-Identification
Yongxing Dai
Jun Liu
Yan Bai
Zekun Tong
Ling-yu Duan
26
77
0
26 Dec 2020
A Second-Order Approach to Learning with Instance-Dependent Label Noise
A Second-Order Approach to Learning with Instance-Dependent Label Noise
Zhaowei Zhu
Tongliang Liu
Yang Liu
NoLa
22
126
0
22 Dec 2020
From Weakly Supervised Learning to Biquality Learning: an Introduction
From Weakly Supervised Learning to Biquality Learning: an Introduction
Pierre Nodet
V. Lemaire
A. Bondu
Antoine Cornuéjols
A. Ouorou
19
21
0
16 Dec 2020
Beyond Class-Conditional Assumption: A Primary Attempt to Combat
  Instance-Dependent Label Noise
Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise
Pengfei Chen
Junjie Ye
Guangyong Chen
Jingwei Zhao
Pheng-Ann Heng
NoLa
40
123
0
10 Dec 2020
Multi-Objective Interpolation Training for Robustness to Label Noise
Multi-Objective Interpolation Training for Robustness to Label Noise
Diego Ortego
Eric Arazo
Paul Albert
Noel E. O'Connor
Kevin McGuinness
NoLa
30
112
0
08 Dec 2020
Robustness of Accuracy Metric and its Inspirations in Learning with
  Noisy Labels
Robustness of Accuracy Metric and its Inspirations in Learning with Noisy Labels
Pengfei Chen
Junjie Ye
Guangyong Chen
Jingwei Zhao
Pheng-Ann Heng
NoLa
103
34
0
08 Dec 2020
The Emerging Trends of Multi-Label Learning
The Emerging Trends of Multi-Label Learning
Weiwei Liu
Haobo Wang
Xiaobo Shen
Ivor W. Tsang
38
252
0
23 Nov 2020
A Survey of Label-noise Representation Learning: Past, Present and
  Future
A Survey of Label-noise Representation Learning: Past, Present and Future
Bo Han
Quanming Yao
Tongliang Liu
Gang Niu
Ivor W. Tsang
James T. Kwok
Masashi Sugiyama
NoLa
24
159
0
09 Nov 2020
Pointwise Binary Classification with Pairwise Confidence Comparisons
Pointwise Binary Classification with Pairwise Confidence Comparisons
Lei Feng
Senlin Shu
Nan Lu
Bo Han
Miao Xu
Gang Niu
Bo An
Masashi Sugiyama
36
22
0
05 Oct 2020
Provably Consistent Partial-Label Learning
Provably Consistent Partial-Label Learning
Lei Feng
Jiaqi Lv
Bo Han
Miao Xu
Gang Niu
Xin Geng
Bo An
Masashi Sugiyama
25
141
0
17 Jul 2020
Learning from Noisy Labels with Deep Neural Networks: A Survey
Learning from Noisy Labels with Deep Neural Networks: A Survey
Hwanjun Song
Minseok Kim
Dongmin Park
Yooju Shin
Jae-Gil Lee
NoLa
24
963
0
16 Jul 2020
Part-dependent Label Noise: Towards Instance-dependent Label Noise
Part-dependent Label Noise: Towards Instance-dependent Label Noise
Xiaobo Xia
Tongliang Liu
Bo Han
Nannan Wang
Biwei Huang
Haifeng Liu
Gang Niu
Dacheng Tao
Masashi Sugiyama
NoLa
13
67
0
14 Jun 2020
Meta Transition Adaptation for Robust Deep Learning with Noisy Labels
Meta Transition Adaptation for Robust Deep Learning with Noisy Labels
Jun Shu
Qian Zhao
Zengben Xu
Deyu Meng
NoLa
31
29
0
10 Jun 2020
Rethinking Importance Weighting for Deep Learning under Distribution
  Shift
Rethinking Importance Weighting for Deep Learning under Distribution Shift
Tongtong Fang
Nan Lu
Gang Niu
Masashi Sugiyama
33
137
0
08 Jun 2020
NoiseRank: Unsupervised Label Noise Reduction with Dependence Models
NoiseRank: Unsupervised Label Noise Reduction with Dependence Models
Karishma Sharma
Pinar E. Donmez
Enming Luo
Yan Liu
I. Z. Yalniz
NoLa
65
33
0
15 Mar 2020
Combating noisy labels by agreement: A joint training method with
  co-regularization
Combating noisy labels by agreement: A joint training method with co-regularization
Hongxin Wei
Lei Feng
Xiangyu Chen
Bo An
NoLa
319
499
0
05 Mar 2020
Progressive Identification of True Labels for Partial-Label Learning
Progressive Identification of True Labels for Partial-Label Learning
Jiaqi Lv
Miao Xu
Lei Feng
Gang Niu
Xin Geng
Masashi Sugiyama
19
177
0
19 Feb 2020
Learning with Multiple Complementary Labels
Learning with Multiple Complementary Labels
Lei Feng
Takuo Kaneko
Bo Han
Gang Niu
Bo An
Masashi Sugiyama
20
92
0
30 Dec 2019
Previous
12