Efficient and Adaptive Linear Regression in Semi-Supervised Settings

17 Jan 2017 Abhishek Chakrabortty Tianxi Cai

We consider the linear regression problem under semi-supervised settings wherein the available data typically consists of: (i) a small or moderate sized 'labeled' data, and (ii) a much larger sized 'unlabeled' data. Such data arises naturally from settings where the outcome, unlike the covariates, is expensive to obtain, a frequent scenario in modern studies involving large databases like electronic medical records (EMR)... (read more)

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METHOD TYPE
Linear Regression
Generalized Linear Models