Learning from Noisy Labels with Noise Modeling Network

no code implementations • 1 May 2020 • Zhuolin Jiang, Jan Silovsky, Man-Hung Siu, William Hartmann, Herbert Gish, Sancar Adali

Multi-label image classification has generated significant interest in recent years and the performance of such systems often suffers from the not so infrequent occurrence of incorrect or missing labels in the training data.

General Classification Missing Labels +2

Towards a New Understanding of the Training of Neural Networks with Mislabeled Training Data

no code implementations • 18 Sep 2019 • Herbert Gish, Jan Silovsky, Man-Ling Sung, Man-Hung Siu, William Hartmann, Zhuolin Jiang

This includes results about the ability of the noisy model to make the same decisions as the clean model and the effects of noise on model performance.