https://github.com/GuokaiLiu/Noisy-Labels-Problem-Collection

This is a collection of Papers and Codes for Noisy Labels Problem.
https://github.com/GuokaiLiu/Noisy-Labels-Problem-Collection

Last synced: 2 months ago
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This is a collection of Papers and Codes for Noisy Labels Problem.

• Host: GitHub
• URL: https://github.com/GuokaiLiu/Noisy-Labels-Problem-Collection
• Owner: GuokaiLiu
• Created: 2018-01-30T07:36:27.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2018-02-12T03:31:02.000Z (over 6 years ago)
• Last Synced: 2024-01-29T09:36:15.408Z (5 months ago)
• Language: Jupyter Notebook
• Size: 361 KB
• Stars: 59
• Watchers: 7
• Forks: 16
• Open Issues: 4
• Metadata Files:
  • Readme: README.md

Lists

• Awesome-Learning-with-Label-Noise - Noisy-Labels-Problem-Collection
• Awesome-Learning-with-Label-Noise - Noisy-Labels-Problem-Collection

README

        
# Noisy-Labels-Problem-Collection

This is a collection of Papers and Codes for Noisy Labels Problem. 

**Papers**

- [2013-Learning with Multiple Labels](https://papers.nips.cc/paper/2234-learning-with-multiple-labels.pdf)

- [2013-NIPS-Learning with Noisy Labels](https://papers.nips.cc/paper/5073-learning-with-noisy-labels.pdf)

- [2014-A Comprehensive Introduction to Label Noise](https://www.elen.ucl.ac.be/Proceedings/esann/esannpdf/es2014-10.pdf)**Introduction**

- [2014-IEEE-Classification in the Presence of Label Noise: a Survey](https://pdfs.semanticscholar.org/2c8f/24f859bbbc4193d4d83645ef467bcf25adc2.pdf)**Survey**

- [2015-CVPR-Learning from Massive Noisy Labeled Data for Image Classification](https://www.ics.uci.edu/~yyang8/research/noisy-label/noisy-label-cvpr2015.pdf)

- [2015-CVPR-Training Deep Neural Networks on Noisy Labels with Bootstrapping](https://arxiv.org/abs/1412.6596)

- [2015-ICLR-TRAINING CONVOLUTIONAL NETWORKS WITH NOISY LABELS](https://arxiv.org/abs/1406.2080)

- [2017-ICLR-Training deep neural-networks based on unreliable labels-V1](http://ieeexplore.ieee.org/document/7472164/)

- [2017-ICLR-Training deep neural-networks based on unreliable labels-V1-Poster](https://alanbekker.files.wordpress.com/2016/03/icassp_poster.pdf)

- [2017-ICLR-Training deep neural-networks using a noise adaptation layer-V2](https://openreview.net/forum?id=H12GRgcxg)

- [2017-CVPR-A Light CNN for Deep Face Representation with Noisy Labels](https://arxiv.org/abs/1511.02683)

- [2017-Learning From Noisy Labels With Distillation](openaccess.thecvf.com/content_iccv_2017/html/Li_Learning_From_Noisy_ICCV_2017_paper.html)

- [2017-AAAI-Robust Loss Functions under Label Noise for Deep Neural Networks](https://arxiv.org/abs/1712.09482)

**Github**

- [Search 'Noisy Label' Results](https://github.com/search?p=1&q=noisy+label&type=Repositories&utf8=%E2%9C%93)

- [Noisy Labels with Jupyter  Notebook](https://github.com/udibr/noisy_labels)

- [Noisy Label Neural Network1-Tensorflow](https://github.com/EstherMaria/NoisyLabelNeuralNetwork)

- [Noisy Label Neural Network2-Chainer](https://github.com/Ryo-Ito/Noisy-Labels-Neural-Network)

- [Multi-tasking Learning With Unreliable Labels](https://github.com/debjitpaul/Multi-tasking_Learning_With_Unreliable_Labels)

- [Keras-noisy-lables-finetune](https://github.com/nagash91/keras-noisy-lables-finetune) 

- [Light CNN for Deep Face Recognition, in Tensorflow](https://github.com/yxu0611/Tensorflow-implementation-of-LCNN)

- [Rankpruning](https://github.com/cgnorthcutt/rankpruning)

**Others**

- [Deep Learning Package-Chainer Tutorial](https://docs.chainer.org/en/stable/tutorial/index.html)

- [Paper-Semi-Supervised Learning Literature Survey](http://pages.cs.wisc.edu/~jerryzhu/pub/ssl_survey.pdf)

- [Cross Validated-Classification with Noisy Labels](https://stats.stackexchange.com/questions/218656/classification-with-noisy-labels)