COVER-EL: Class cOVERage-Aware Noise Correction for Crowdsourced Labels via Elimination-Based Inference.
In crowdsourcing scenarios, where each instance is labeled with multiple noisy labels, its true label is estimated by combining label integration and various recently proposed noise correction methods. Recent correction methods typically partition the data into clean and noisy sets, then train classifiers on a high-con...