robust training

Tackling Instance-Dependent Label Noise via a Universal Probabilistic Model AAAI 2021 A Closer Look at Accuracy vs. Robustness NeurIPS 2020 Addressing The False Negative Problem of Deep Learning MRI Reconstruction Models by Adversarial Attacks and Robust Training MIDL 2020 Coresets for Robust Training of Deep Neural Networks against Noisy Labels NeurIPS 2020 Distilling Effective Supervision From Severe Label Noise CVPR 2020 FR-Train: A Mutual Information-Based Approach to Fair and Robust Training ICML 2020 Lipschitz Bounds and Provably Robust Training by Laplacian Smoothing NeurIPS 2020 Robust Federated Learning via Collaborative Machine Teaching AAAI 2020 Robust training with ensemble consensus ICLR 2020 Self-Paced Robust Learning for Leveraging Clean Labels in Noisy Data AAAI 2020 Certifiable Robustness to Graph Perturbations NeurIPS 2019 Robust Person Re-Identification by Modelling Feature Uncertainty ICCV 2019 SELFIE: Refurbishing Unclean Samples for Robust Deep Learning ICML 2019 Co-teaching: Robust training of deep neural networks with extremely noisy labels NeurIPS 2018 Robust and Scalable Differentiable Neural Computer for Question Answering ACL 2018 Synthetic and Natural Noise Both Break Neural Machine Translation ICLR 2018 Making Deep Neural Networks Robust to Label Noise: A Loss Correction Approach CVPR 2017 Unsupervised Extraction of Video Highlights Via Robust Recurrent Auto-Encoders ICCV 2015