Robust Learning

Improving Model Robustness by Adaptively Correcting Perturbation Levels with Active Queries AAAI 2021 Instance-adaptive training with noise-robust losses against noisy labels EMNLP 2021 Jo-SRC: A Contrastive Approach for Combating Noisy Labels CVPR 2021 Learning from Noisy Labels with Complementary Loss Functions AAAI 2021 Outlier-Robust Optimal Transport ICML 2021 ProSelfLC: Progressive Self Label Correction for Training Robust Deep Neural Networks CVPR 2021 Robust learning under clean-label attack COLT 2021 Tackling Instance-Dependent Label Noise via a Universal Probabilistic Model AAAI 2021 Tilted Empirical Risk Minimization ICLR 2021 Distilling Effective Supervision From Severe Label Noise CVPR 2020 Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning NeurIPS 2020 Learning Robust Decision Policies from Observational Data NeurIPS 2020 Learning Robust Models for e-Commerce Product Search ACL 2020 List-Decodable Mean Estimation via Iterative Multi-Filtering NeurIPS 2020 List Decodable Subspace Recovery COLT 2020 Noise-tolerant, Reliable Active Classification with Comparison Queries COLT 2020 On Learning Ising Models under Huber's Contamination Model NeurIPS 2020 Reinforcement Learning with Perturbed Rewards AAAI 2020 Robust Deep Ordinal Regression under Label Noise ACML 2020 Sinkhorn Regression IJCAI 2020 Learning and the Unknown: Surveying Steps toward Open World Recognition AAAI 2019 Learning from Bad Data via Generation NeurIPS 2019 List-decodable Linear Regression NeurIPS 2019 Do Outliers Ruin Collaboration? ICML 2018 Robust Estimation of Neural Signals in Calcium Imaging NeurIPS 2017