Learning to Learn from Weak Supervision by Full Supervision
Our paper "Learning to Learn from Weak Supervision by Full Supervision", with Sascha Rothe, and Jaap Kamps, has been accepted at NIPS2017 Workshop on Meta-Learning (MetaLearn 2017). \o/ Using weak or noisy supervision is a straightforward approach to increase the size of the training data and it has been shown that the output of heuristic […]