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Deep k-NN for Noisy Labels

Deep k-NN for Noisy Labels

26 April 2020
Dara Bahri
Heinrich Jiang
Maya R. Gupta
    NoLa
ArXivPDFHTML

Papers citing "Deep k-NN for Noisy Labels"

19 / 19 papers shown
Title
An Embedding is Worth a Thousand Noisy Labels
An Embedding is Worth a Thousand Noisy Labels
Francesco Di Salvo
Sebastian Doerrich
Ines Rieger
Christian Ledig
NoLa
75
0
0
26 Aug 2024
Learning with Noisy Labels through Learnable Weighting and Centroid
  Similarity
Learning with Noisy Labels through Learnable Weighting and Centroid Similarity
F. Wani
Maria Sofia Bucarelli
Fabrizio Silvestri
NoLa
37
3
0
16 Mar 2023
Denoising after Entropy-based Debiasing A Robust Training Method for
  Dataset Bias with Noisy Labels
Denoising after Entropy-based Debiasing A Robust Training Method for Dataset Bias with Noisy Labels
Sumyeong Ahn
Se-Young Yun
NoLa
33
2
0
01 Dec 2022
Towards Harnessing Feature Embedding for Robust Learning with Noisy
  Labels
Towards Harnessing Feature Embedding for Robust Learning with Noisy Labels
Chuang Zhang
Li Shen
Jian Yang
Chen Gong
NoLa
27
5
0
27 Jun 2022
Context-based Virtual Adversarial Training for Text Classification with
  Noisy Labels
Context-based Virtual Adversarial Training for Text Classification with Noisy Labels
Do-Myoung Lee
Yeachan Kim
Chang-gyun Seo
NoLa
21
2
0
29 May 2022
Learning with Neighbor Consistency for Noisy Labels
Learning with Neighbor Consistency for Noisy Labels
Ahmet Iscen
Jack Valmadre
Anurag Arnab
Cordelia Schmid
NoLa
41
75
0
04 Feb 2022
SSR: An Efficient and Robust Framework for Learning with Unknown Label
  Noise
SSR: An Efficient and Robust Framework for Learning with Unknown Label Noise
Chen Feng
Georgios Tzimiropoulos
Ioannis Patras
NoLa
27
18
0
22 Nov 2021
Detecting Corrupted Labels Without Training a Model to Predict
Detecting Corrupted Labels Without Training a Model to Predict
Zhaowei Zhu
Zihao Dong
Yang Liu
NoLa
149
62
0
12 Oct 2021
Label Cleaning Multiple Instance Learning: Refining Coarse Annotations
  on Single Whole-Slide Images
Label Cleaning Multiple Instance Learning: Refining Coarse Annotations on Single Whole-Slide Images
Zhenzhen Wang
Carla Saoud
A. Popel
Aaron W. James
Aleksander S. Popel
Jeremias Sulam
21
21
0
22 Sep 2021
kNet: A Deep kNN Network To Handle Label Noise
kNet: A Deep kNN Network To Handle Label Noise
Itzik Mizrahi
S. Avidan
NoLa
21
0
0
20 Jul 2021
SCARF: Self-Supervised Contrastive Learning using Random Feature
  Corruption
SCARF: Self-Supervised Contrastive Learning using Random Feature Corruption
Dara Bahri
Heinrich Jiang
Yi Tay
Donald Metzler
SSL
21
164
0
29 Jun 2021
Deep Learning Through the Lens of Example Difficulty
Deep Learning Through the Lens of Example Difficulty
R. Baldock
Hartmut Maennel
Behnam Neyshabur
47
156
0
17 Jun 2021
FINE Samples for Learning with Noisy Labels
FINE Samples for Learning with Noisy Labels
Taehyeon Kim
Jongwoo Ko
Sangwook Cho
J. Choi
Se-Young Yun
NoLa
38
103
0
23 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
Locally Adaptive Label Smoothing for Predictive Churn
Locally Adaptive Label Smoothing for Predictive Churn
Dara Bahri
Heinrich Jiang
NoLa
43
8
0
09 Feb 2021
A Topological Filter for Learning with Label Noise
A Topological Filter for Learning with Label Noise
Pengxiang Wu
Songzhu Zheng
Mayank Goswami
Dimitris N. Metaxas
Chao Chen
NoLa
30
112
0
09 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
Certified Robustness of Nearest Neighbors against Data Poisoning and
  Backdoor Attacks
Certified Robustness of Nearest Neighbors against Data Poisoning and Backdoor Attacks
Jinyuan Jia
Yupei Liu
Xiaoyu Cao
Neil Zhenqiang Gong
AAML
40
73
0
07 Dec 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
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