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Uncertainty-Aware Learning Against Label Noise on Imbalanced Datasets

Uncertainty-Aware Learning Against Label Noise on Imbalanced Datasets

12 July 2022
Yingsong Huang
Bing Bai
Shengwei Zhao
Kun Bai
Fei Wang
    NoLa
ArXivPDFHTML

Papers citing "Uncertainty-Aware Learning Against Label Noise on Imbalanced Datasets"

22 / 22 papers shown
Title
Uncertainty Quantification for Machine Learning in Healthcare: A Survey
Uncertainty Quantification for Machine Learning in Healthcare: A Survey
L. J. L. Lopez
Shaza Elsharief
Dhiyaa Al Jorf
Firas Darwish
Congbo Ma
Farah E. Shamout
175
0
0
04 May 2025
Classifying Long-tailed and Label-noise Data via Disentangling and Unlearning
Chen Shu
Mengke Li
Yiqun Zhang
Yang Lu
Bo Han
Yiu-ming Cheung
Hanzi Wang
NoLa
70
0
0
14 Mar 2025
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
45
1
0
03 Nov 2024
Self-Relaxed Joint Training: Sample Selection for Severity Estimation
  with Ordinal Noisy Labels
Self-Relaxed Joint Training: Sample Selection for Severity Estimation with Ordinal Noisy Labels
Shumpei Takezaki
Kiyohito Tanaka
S. Uchida
NoLa
35
0
0
29 Oct 2024
Estimating Noisy Class Posterior with Part-level Labels for Noisy Label
  Learning
Estimating Noisy Class Posterior with Part-level Labels for Noisy Label Learning
Rui Zhao
Bin Shi
Jianfei Ruan
Tianze Pan
Bo Dong
NoLa
34
5
0
08 May 2024
Extracting Clean and Balanced Subset for Noisy Long-tailed
  Classification
Extracting Clean and Balanced Subset for Noisy Long-tailed Classification
Zhuo Li
He Zhao
Zhen Li
Tongliang Liu
Dandan Guo
Xiang Wan
NoLa
46
1
0
10 Apr 2024
Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy
  Label Learning
Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning
Heesun Bae
Seungjae Shin
Byeonghu Na
Il-Chul Moon
NoLa
46
3
0
05 Mar 2024
Addressing Long-Tail Noisy Label Learning Problems: a Two-Stage Solution
  with Label Refurbishment Considering Label Rarity
Addressing Long-Tail Noisy Label Learning Problems: a Two-Stage Solution with Label Refurbishment Considering Label Rarity
Ying-Hsuan Wu
Jun-Wei Hsieh
Li Xin
Shin-You Teng
Yi-Kuan Hsieh
Ming-Ching Chang
NoLa
51
0
0
04 Mar 2024
On the use of Silver Standard Data for Zero-shot Classification Tasks in
  Information Extraction
On the use of Silver Standard Data for Zero-shot Classification Tasks in Information Extraction
Jianwei Wang
Tianyin Wang
Ziqian Zeng
60
1
0
28 Feb 2024
Learning with Imbalanced Noisy Data by Preventing Bias in Sample
  Selection
Learning with Imbalanced Noisy Data by Preventing Bias in Sample Selection
Huafeng Liu
Mengmeng Sheng
Zeren Sun
Yazhou Yao
Xian-Sheng Hua
H. Shen
NoLa
26
6
0
17 Feb 2024
Training of Neural Networks with Uncertain Data: A Mixture of Experts
  Approach
Training of Neural Networks with Uncertain Data: A Mixture of Experts Approach
Lucas Luttner
UQCV
26
1
0
13 Dec 2023
Expert Uncertainty and Severity Aware Chest X-Ray Classification by
  Multi-Relationship Graph Learning
Expert Uncertainty and Severity Aware Chest X-Ray Classification by Multi-Relationship Graph Learning
Mengliang Zhang
Xinyue Hu
Lin Gu
Liangchen Liu
Kazuma Kobayashi
Tatsuya Harada
Ronald M. Summers
Yingying Zhu
33
3
0
06 Sep 2023
Unbiased Scene Graph Generation in Videos
Unbiased Scene Graph Generation in Videos
Sayak Nag
Kyle Min
Subarna Tripathi
A. Roy-Chowdhury
34
29
0
03 Apr 2023
Instance-specific Label Distribution Regularization for Learning with
  Label Noise
Instance-specific Label Distribution Regularization for Learning with Label Noise
Zehui Liao
Shishuai Hu
Yutong Xie
Yong-quan Xia
NoLa
26
3
0
16 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
Rethinking Missing Data: Aleatoric Uncertainty-Aware Recommendation
Rethinking Missing Data: Aleatoric Uncertainty-Aware Recommendation
Chenxu Wang
Fuli Feng
Yang Zhang
Qifan Wang
Xu Hu
Xiangnan He
52
8
0
22 Sep 2022
Label-Noise Learning with Intrinsically Long-Tailed Data
Label-Noise Learning with Intrinsically Long-Tailed Data
Yang Lu
Yiliang Zhang
Bo Han
Y. Cheung
Hanzi Wang
NoLa
48
17
0
21 Aug 2022
ProMix: Combating Label Noise via Maximizing Clean Sample Utility
ProMix: Combating Label Noise via Maximizing Clean Sample Utility
Rui Xiao
Yiwen Dong
Haobo Wang
Lei Feng
Runze Wu
Gang Chen
Jun Zhao
24
54
0
21 Jul 2022
In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label
  Selection Framework for Semi-Supervised Learning
In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning
Mamshad Nayeem Rizve
Kevin Duarte
Yogesh S Rawat
M. Shah
247
509
0
15 Jan 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
276
5,683
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
287
9,156
0
06 Jun 2015
SMOTE: Synthetic Minority Over-sampling Technique
SMOTE: Synthetic Minority Over-sampling Technique
Nitesh V. Chawla
Kevin W. Bowyer
Lawrence Hall
W. Kegelmeyer
AI4TS
163
25,296
0
09 Jun 2011
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