Robust bi-tempered logistic loss based on bregman divergences, ArXiv, 2019. ,
Generalized cross entropy loss for training deep neural networks with noisy labels, 2018. ,
Classification in the presence of label noise: A survey, IEEE Transactions on Neural Networks and Learning Systems, vol.25, pp.845-869, 2014. ,
Lof: Identifying density-based local outliers, SIGMOD Conference, 2000. ,
Cifar-10 (canadian institute for advanced research) ,
MNIST handwritten digit database, 2010. ,
Learning from massive noisy labeled data for image classification, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.2691-2699, 2015. ,
Cleannet: Transfer learning for scalable image classifier training with label noise, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.5447-5456, 2017. ,
Webvision database: Visual learning and understanding from web data, ArXiv, 2017. ,
ImageNet: A Large-Scale Hierarchical Image Database, p.9, 2009. ,
Deep residual learning for image recognition, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.770-778, 2015. ,
Going deeper with convolutions, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.1-9, 2014. ,
Very deep convolutional networks for large-scale image recognition, CoRR, 2014. ,
Nlnl: Negative learning for noisy labels, ArXiv, 2019. ,
Robust learning under label noise with iterative noisefiltering, ArXiv, 2019. ,
Learning to reweight examples for robust deep learning, ArXiv, 2018. ,
Iterative learning with open-set noisy labels, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.8688-8696, 2018. ,
Training deep neural-networks based on unreliable labels, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.2682-2686, 2016. ,
Using trusted data to train deep networks on labels corrupted by severe noise, 2018. ,
Deep self-learning from noisy labels, ArXiv, 2019. ,
Curriculumnet: Weakly supervised learning from large-scale web images, ArXiv, 2018. ,
Co-mining: Deep face recognition with noisy labels ,
Mixmatch: A holistic approach to semi-supervised learning, ArXiv, 2019. ,
Unsupervised data augmentation, ArXiv, 2019. ,