Co-occurring keywords · papers mentioning both
Papers
SELF: Learning to Filter Noisy Labels with Self-Ensembling
ICLR 2020
Task Agnostic Robust Learning on Corrupt Outputs by Correlation-Guided Mixture Density Networks
CVPR 2020
Web-Supervised Network with Softly Update-Drop Training for Fine-Grained Visual Classification
AAAI 2020
Data Parameters: A New Family of Parameters for Learning a Differentiable Curriculum
NeurIPS 2019
Learning From Noisy Labels by Regularized Estimation of Annotator Confusion
CVPR 2019
Learning to Learn From Noisy Labeled Data
CVPR 2019
Learning with Noisy Labels for Sentence-level Sentiment Classification
EMNLP 2019
MetaCleaner: Learning to Hallucinate Clean Representations for Noisy-Labeled Visual Recognition
CVPR 2019
Modelling Instance-Level Annotator Reliability for Natural Language Labelling Tasks
NAACL 2019
Probabilistic End-To-End Noise Correction for Learning With Noisy Labels
CVPR 2019
Safeguarded Dynamic Label Regression for Noisy Supervision
AAAI 2019
SELFIE: Refurbishing Unclean Samples for Robust Deep Learning
ICML 2019
Iterative Learning With Open-Set Noisy Labels
CVPR 2018
Put It Back: Entity Typing with Language Model Enhancement
EMNLP 2018
Decoupling "when to update" from "how to update"
NeurIPS 2017
Learning From Noisy Large-Scale Datasets With Minimal Supervision
CVPR 2017
Learning Time Series Detection Models from Temporally Imprecise Labels
AISTATS 2017
Learning to Learn From Noisy Web Videos
CVPR 2017
Noisy Label Recovery for Shadow Detection in Unfamiliar Domains
CVPR 2016
Learning From Massive Noisy Labeled Data for Image Classification
CVPR 2015
Learning with Noisy Labels
NeurIPS 2013