Semi-supervised Learning based on Distributionally Robust Optimization

28 Feb 2017Jose BlanchetYang Kang

We propose a novel method for semi-supervised learning (SSL) based on data-driven distributionally robust optimization (DRO) using optimal transport metrics. Our proposed method enhances generalization error by using the unlabeled data to restrict the support of the worst case distribution in our DRO formulation... (read more)

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