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Duncan Wilson

1 accepted papers

2018

Using Trusted Data to Train Deep Networks on Labels Corrupted by Severe Noise

NeurIPS 2018poster

The growing importance of massive datasets with the advent of deep learning makes robustness to label noise a critical property for classifiers to have. Sources of label noise include automatic labeling for large datasets, non-expert labeling, and label corruption by data poisoning adversaries. In t…