Collaborative learning with corrupted labels

Deep neural networks (DNNs) have been very successful for supervised learning. However, their high generalization performance often comes with the high cost of annotating data manually. Collecting low-quality labeled dataset is relatively cheap, e.g., using web search engines, while DNNs tend to overfit to corrupted labels easily. In this...More