2016
Asking for a second opinion: Re-querying of noisy multi-class labels
ICASSP 2016accepted
In this paper, we propose a new maximum margin-based, active learning algorithm for identifying incorrectly labeled training data. The algorithm combines a round-robin approach for investigating each class with a simple, yet effective ranking metric called maximum negative margin (MNM). Samples are…