Robust Prediction when Features are Missing

16 Dec 2019Xiuming LiuDave ZachariahPetre Stoica

Predictors are learned using past training data which may contain features that are unavailable at the time of prediction. We develop an approach that is robust against outlying missing features, based on the optimality properties of an oracle predictor which observes them... (read more)

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