An joint end-to-end framework for learning with noisy labels

Deep Residual Learning for Image Recognition

Kaiming He, Xiangyu Zhang, Shaoqing Ren et al. · 2016 · 222.1K citations · Full text

Computing, Computer Science, Computer Vision +11

mixup: Beyond Empirical Risk Minimization

Hongyi Zhang, Moustapha Cissé, Yann Dauphin et al. · arXiv (Cornell University) · 2017 · 4.8K citations · Full text

Computing, Computer Science, Artificial Intelligence +13

Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels

Zhilu Zhang, Mert R. Sabuncu · PubMed · 2018 · 1.5K citations · Full text

Computing, Computer Science, Artificial Intelligence +16

Making Deep Neural Networks Robust to Label Noise: A Loss Correction Approach

Giorgio Patrini, Alessandro Rozza, Aditya Krishna Menon et al. · 2017 · 1.4K citations

Computing, Computer Science, Computer Vision +16

Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels

Bo Han, Quanming Yao, Xingrui Yu et al. · Neural Information Processing Systems · 2018 · 1.2K citations

Computing, Computer Science, Machine Learning +10