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Multi-Objective Interpolation Training for Robustness to Label Noise

Multi-Objective Interpolation Training for Robustness to Label Noise

8 December 2020
Diego Ortego
Eric Arazo
Paul Albert
Noel E. O'Connor
Kevin McGuinness
    NoLa
ArXivPDFHTML

Papers citing "Multi-Objective Interpolation Training for Robustness to Label Noise"

50 / 72 papers shown
Title
Sample Selection via Contrastive Fragmentation for Noisy Label Regression
Sample Selection via Contrastive Fragmentation for Noisy Label Regression
C. Kim
Sangwoo Moon
Jihwan Moon
Dongyeon Woo
Gunhee Kim
NoLa
57
0
0
25 Feb 2025
Set a Thief to Catch a Thief: Combating Label Noise through Noisy Meta Learning
Set a Thief to Catch a Thief: Combating Label Noise through Noisy Meta Learning
Hanxuan Wang
Na Lu
Xueying Zhao
Yuxuan Yan
Kaipeng Ma
Kwoh Chee Keong
Gustavo Carneiro
NoLa
59
0
0
22 Feb 2025
Open set label noise learning with robust sample selection and margin-guided module
Open set label noise learning with robust sample selection and margin-guided module
Yuandi Zhao
Qianxi Xia
Yang Sun
Zhijie Wen
Liyan Ma
Shihui Ying
NoLa
46
0
0
08 Jan 2025
An Inclusive Theoretical Framework of Robust Supervised Contrastive Loss against Label Noise
Jingyi Cui
Yi-Ge Zhang
Hengyu Liu
Yisen Wang
NoLa
45
0
0
03 Jan 2025
Combating Label Noise With A General Surrogate Model For Sample Selection
Combating Label Noise With A General Surrogate Model For Sample Selection
Chao Liang
Linchao Zhu
Humphrey Shi
Yi Yang
VLM
NoLa
46
2
0
31 Dec 2024
ANNE: Adaptive Nearest Neighbors and Eigenvector-based Sample Selection
  for Robust Learning with Noisy Labels
ANNE: Adaptive Nearest Neighbors and Eigenvector-based Sample Selection for Robust Learning with Noisy Labels
F. Cordeiro
G. Carneiro
NoLa
40
1
0
03 Nov 2024
CLIPCleaner: Cleaning Noisy Labels with CLIP
CLIPCleaner: Cleaning Noisy Labels with CLIP
Chen Feng
Georgios Tzimiropoulos
Ioannis Patras
VLM
35
1
0
19 Aug 2024
Learning to Complement and to Defer to Multiple Users
Learning to Complement and to Defer to Multiple Users
Zheng Zhang
Wenjie Ai
Kevin Wells
David Rosewarne
Thanh-Toan Do
Gustavo Carneiro
53
0
0
09 Jul 2024
An accurate detection is not all you need to combat label noise in
  web-noisy datasets
An accurate detection is not all you need to combat label noise in web-noisy datasets
Paul Albert
Jack Valmadre
Eric Arazo
Tarun Krishna
Noel E. O'Connor
Kevin McGuinness
AAML
43
0
0
08 Jul 2024
Label Noise Robustness for Domain-Agnostic Fair Corrections via Nearest
  Neighbors Label Spreading
Label Noise Robustness for Domain-Agnostic Fair Corrections via Nearest Neighbors Label Spreading
Nathan Stromberg
Rohan Ayyagari
Sanmi Koyejo
Richard Nock
Lalitha Sankar
46
0
0
13 Jun 2024
Rethinking the impact of noisy labels in graph classification: A utility
  and privacy perspective
Rethinking the impact of noisy labels in graph classification: A utility and privacy perspective
De Li
Xianxian Li
Zeming Gan
Qiyu Li
Bin Qu
Jinyan Wang
NoLa
45
1
0
11 Jun 2024
EEG-MACS: Manifold Attention and Confidence Stratification for EEG-based
  Cross-Center Brain Disease Diagnosis under Unreliable Annotations
EEG-MACS: Manifold Attention and Confidence Stratification for EEG-based Cross-Center Brain Disease Diagnosis under Unreliable Annotations
Zhenxi Song
Ruihan Qin
Huixia Ren
Zhen Liang
Yi Guo
Min Zhang
Zhiguo Zhang
21
1
0
29 Apr 2024
Robust Noisy Label Learning via Two-Stream Sample Distillation
Robust Noisy Label Learning via Two-Stream Sample Distillation
Sihan Bai
Sanpin Zhou
Zheng Qin
Le Wang
Nanning Zheng
NoLa
27
0
0
16 Apr 2024
QMix: Quality-aware Learning with Mixed Noise for Robust Retinal Disease Diagnosis
QMix: Quality-aware Learning with Mixed Noise for Robust Retinal Disease Diagnosis
Junlin Hou
Jilan Xu
Rui Feng
Hao Chen
23
0
0
08 Apr 2024
Noisy Label Processing for Classification: A Survey
Noisy Label Processing for Classification: A Survey
Mengting Li
Chuang Zhu
NoLa
40
1
0
05 Apr 2024
Pairwise Similarity Distribution Clustering for Noisy Label Learning
Pairwise Similarity Distribution Clustering for Noisy Label Learning
Sihan Bai
NoLa
24
0
0
02 Apr 2024
Uncertainty-Aware Pseudo-Label Filtering for Source-Free Unsupervised
  Domain Adaptation
Uncertainty-Aware Pseudo-Label Filtering for Source-Free Unsupervised Domain Adaptation
Xi Chen
Haosen Yang
Huicong Zhang
Hongxun Yao
Xiatian Zhu
41
2
0
17 Mar 2024
REPAIR: Rank Correlation and Noisy Pair Half-replacing with Memory for
  Noisy Correspondence
REPAIR: Rank Correlation and Noisy Pair Half-replacing with Memory for Noisy Correspondence
Ruochen Zheng
Jiahao Hong
Changxin Gao
Nong Sang
36
1
0
13 Mar 2024
PLReMix: Combating Noisy Labels with Pseudo-Label Relaxed Contrastive
  Representation Learning
PLReMix: Combating Noisy Labels with Pseudo-Label Relaxed Contrastive Representation Learning
Xiaoyu Liu
Beitong Zhou
Cheng Cheng
37
3
0
27 Feb 2024
Pseudo-labelling meets Label Smoothing for Noisy Partial Label Learning
Pseudo-labelling meets Label Smoothing for Noisy Partial Label Learning
Darshana Saravanan
Naresh Manwani
Vineet Gandhi
28
0
0
07 Feb 2024
Dirichlet-Based Prediction Calibration for Learning with Noisy Labels
Dirichlet-Based Prediction Calibration for Learning with Noisy Labels
Chen-Chen Zong
Ye-Wen Wang
Ming-Kun Xie
Sheng-Jun Huang
21
5
0
13 Jan 2024
Learning with Noisy Labels: Interconnection of Two
  Expectation-Maximizations
Learning with Noisy Labels: Interconnection of Two Expectation-Maximizations
Heewon Kim
Hyun Sung Chang
Kiho Cho
Jaeyun Lee
Bohyung Han
NoLa
26
2
0
09 Jan 2024
Regroup Median Loss for Combating Label Noise
Regroup Median Loss for Combating Label Noise
Fengpeng Li
Kemou Li
Jinyu Tian
Jiantao Zhou
NoLa
41
2
0
11 Dec 2023
CSOT: Curriculum and Structure-Aware Optimal Transport for Learning with
  Noisy Labels
CSOT: Curriculum and Structure-Aware Optimal Transport for Learning with Noisy Labels
Wanxing Chang
Ye-ling Shi
Jingya Wang
OT
38
12
0
11 Dec 2023
Elucidating and Overcoming the Challenges of Label Noise in Supervised
  Contrastive Learning
Elucidating and Overcoming the Challenges of Label Noise in Supervised Contrastive Learning
Zijun Long
George Killick
Lipeng Zhuang
R. McCreadie
Gerardo Aragon Camarasa
Paul Henderson
30
5
0
25 Nov 2023
Learning to Complement with Multiple Humans
Learning to Complement with Multiple Humans
Zheng Zhang
Cuong C. Nguyen
Kevin Wells
Thanh-Toan Do
Gustavo Carneiro
24
0
0
22 Nov 2023
Learning with Noisy Labels Using Collaborative Sample Selection and
  Contrastive Semi-Supervised Learning
Learning with Noisy Labels Using Collaborative Sample Selection and Contrastive Semi-Supervised Learning
Qing Miao
Xiaohe Wu
Chao Xu
Yanli Ji
Wangmeng Zuo
Yiwen Guo
Zhaopeng Meng
NoLa
29
2
0
24 Oct 2023
CAPro: Webly Supervised Learning with Cross-Modality Aligned Prototypes
CAPro: Webly Supervised Learning with Cross-Modality Aligned Prototypes
Yulei Qin
Xingyu Chen
Yunhang Shen
Chaoyou Fu
Yun Gu
Ke Li
Xing Sun
Rongrong Ji
36
3
0
15 Oct 2023
Towards Robust Few-shot Point Cloud Semantic Segmentation
Towards Robust Few-shot Point Cloud Semantic Segmentation
Yating Xu
Na Zhao
Gim Hee Lee
3DPC
18
3
0
20 Sep 2023
Manifold DivideMix: A Semi-Supervised Contrastive Learning Framework for
  Severe Label Noise
Manifold DivideMix: A Semi-Supervised Contrastive Learning Framework for Severe Label Noise
Fahimeh Fooladgar
Minh Nguyen Nhat To
P. Mousavi
Purang Abolmaesumi
NoLa
32
4
0
13 Aug 2023
Partial Label Supervision for Agnostic Generative Noisy Label Learning
Partial Label Supervision for Agnostic Generative Noisy Label Learning
Fengbei Liu
Chong Wang
Yuanhong Chen
Yuyuan Liu
G. Carneiro
NoLa
30
1
0
02 Aug 2023
LaplaceConfidence: a Graph-based Approach for Learning with Noisy Labels
LaplaceConfidence: a Graph-based Approach for Learning with Noisy Labels
Mingcai Chen
Yuntao Du
Wei Tang
Baoming Zhang
Hao Cheng
Shuwei Qian
Chongjun Wang
NoLa
19
1
0
31 Jul 2023
MILD: Modeling the Instance Learning Dynamics for Learning with Noisy
  Labels
MILD: Modeling the Instance Learning Dynamics for Learning with Noisy Labels
Chuanyan Hu
Shipeng Yan
Zhitong Gao
Xuming He
NoLa
24
4
0
20 Jun 2023
Rethinking Weak Supervision in Helping Contrastive Learning
Rethinking Weak Supervision in Helping Contrastive Learning
Jingyi Cui
Weiran Huang
Yifei Wang
Yisen Wang
NoLa
SSL
32
13
0
07 Jun 2023
Unlocking the Power of Open Set : A New Perspective for Open-Set Noisy
  Label Learning
Unlocking the Power of Open Set : A New Perspective for Open-Set Noisy Label Learning
Wenhai Wan
Xinrui Wang
Ming-Kun Xie
Shao-Yuan Li
Sheng-Jun Huang
Songcan Chen
33
8
0
07 May 2023
A Survey of Historical Learning: Learning Models with Learning History
A Survey of Historical Learning: Learning Models with Learning History
Xiang Li
Ge Wu
Lingfeng Yang
Wenzhe Wang
Renjie Song
Jian Yang
MU
AI4TS
28
2
0
23 Mar 2023
Twin Contrastive Learning with Noisy Labels
Twin Contrastive Learning with Noisy Labels
Zhizhong Huang
Junping Zhang
Hongming Shan
NoLa
6
53
0
13 Mar 2023
Learning from Noisy Labels with Decoupled Meta Label Purifier
Learning from Noisy Labels with Decoupled Meta Label Purifier
Yuanpeng Tu
Boshen Zhang
Yuxi Li
Liang Liu
Jian Li
Yabiao Wang
Chengjie Wang
C. Zhao
NoLa
49
27
0
14 Feb 2023
Learning with Noisy labels via Self-supervised Adversarial Noisy Masking
Learning with Noisy labels via Self-supervised Adversarial Noisy Masking
Yuanpeng Tu
Boshen Zhang
Yuxi Li
Liang Liu
Jian Li
Jiangning Zhang
Yabiao Wang
Chengjie Wang
C. Zhao
AAML
NoLa
38
15
0
14 Feb 2023
Towards the Identifiability in Noisy Label Learning: A Multinomial
  Mixture Approach
Towards the Identifiability in Noisy Label Learning: A Multinomial Mixture Approach
Cuong C. Nguyen
Thanh-Toan Do
G. Carneiro
NoLa
32
0
0
04 Jan 2023
Truncate-Split-Contrast: A Framework for Learning from Mislabeled Videos
Truncate-Split-Contrast: A Framework for Learning from Mislabeled Videos
Zixiao Wang
Junwu Weng
C. Yuan
Jue Wang
NoLa
27
4
0
27 Dec 2022
CrossSplit: Mitigating Label Noise Memorization through Data Splitting
CrossSplit: Mitigating Label Noise Memorization through Data Splitting
Jihye Kim
A. Baratin
Yan Zhang
Simon Lacoste-Julien
NoLa
18
7
0
03 Dec 2022
Dynamic Loss For Robust Learning
Dynamic Loss For Robust Learning
Shenwang Jiang
Jianan Li
Jizhou Zhang
Ying Wang
Tingfa Xu
NoLa
OOD
28
6
0
22 Nov 2022
Learning with Noisy Labels over Imbalanced Subpopulations
Learning with Noisy Labels over Imbalanced Subpopulations
Mingcai Chen
Yu Zhao
Bing He
Zongbo Han
Bingzhe Wu
Jianhua Yao
26
8
0
16 Nov 2022
Bootstrapping the Relationship Between Images and Their Clean and Noisy
  Labels
Bootstrapping the Relationship Between Images and Their Clean and Noisy Labels
Brandon Smart
G. Carneiro
NoLa
26
11
0
17 Oct 2022
Tackling Instance-Dependent Label Noise with Dynamic Distribution
  Calibration
Tackling Instance-Dependent Label Noise with Dynamic Distribution Calibration
Manyi Zhang
Yuxin Ren
Zihao Wang
C. Yuan
21
3
0
11 Oct 2022
An Action Is Worth Multiple Words: Handling Ambiguity in Action
  Recognition
An Action Is Worth Multiple Words: Handling Ambiguity in Action Recognition
Kiyoon Kim
Davide Moltisanti
Oisin Mac Aodha
Laura Sevilla-Lara
16
0
0
10 Oct 2022
Is your noise correction noisy? PLS: Robustness to label noise with two
  stage detection
Is your noise correction noisy? PLS: Robustness to label noise with two stage detection
Paul Albert
Eric Arazo
Tarun Kirshna
Noel E. O'Connor
Kevin McGuinness
NoLa
24
14
0
10 Oct 2022
The Dynamic of Consensus in Deep Networks and the Identification of
  Noisy Labels
The Dynamic of Consensus in Deep Networks and the Identification of Noisy Labels
Daniel Shwartz
Uri Stern
D. Weinshall
NoLa
33
2
0
02 Oct 2022
Combating Noisy Labels in Long-Tailed Image Classification
Combating Noisy Labels in Long-Tailed Image Classification
Chaowei Fang
Lechao Cheng
Huiyan Qi
Dingwen Zhang
NoLa
17
2
0
01 Sep 2022
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