noisy label

Uncover the Ground-Truth Relations in Distant Supervision: A Neural Expectation-Maximization Framework EMNLP 2019 Active Testing: An Efficient and Robust Framework for Estimating Accuracy ICML 2018 A Theory of Learning with Corrupted Labels JMLR 2018 Certified Computation from Unreliable Datasets COLT 2018 CleanNet: Transfer Learning for Scalable Image Classifier Training With Label Noise CVPR 2018 Cost-Sensitive Learning with Noisy Labels JMLR 2018 Co-teaching: Robust training of deep neural networks with extremely noisy labels NeurIPS 2018 Deep Unsupervised Saliency Detection: A Multiple Noisy Labeling Perspective CVPR 2018 Dimensionality-Driven Learning with Noisy Labels ICML 2018 Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels NeurIPS 2018 Iterative Learning With Open-Set Noisy Labels CVPR 2018 Joint Optimization Framework for Learning With Noisy Labels CVPR 2018 Learning From Noisy Singly-labeled Data ICLR 2018 Masking: A New Perspective of Noisy Supervision NeurIPS 2018 MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels ICML 2018 Put It Back: Entity Typing with Language Model Enhancement EMNLP 2018 Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias NeurIPS 2018 Robust Active Label Correction AISTATS 2018 Robustness of conditional GANs to noisy labels NeurIPS 2018 Semi-crowdsourced Clustering with Deep Generative Models NeurIPS 2018 Training and Prediction Data Discrepancies: Challenges of Text Classification with Noisy, Historical Data EMNLP 2018 Training a Neural Network in a Low-Resource Setting on Automatically Annotated Noisy Data ACL 2018 Attend in Groups: A Weakly-Supervised Deep Learning Framework for Learning From Web Data CVPR 2017 Decoupling "when to update" from "how to update" NeurIPS 2017 Heterogeneous Supervision for Relation Extraction: A Representation Learning Approach EMNLP 2017