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Robust Prediction when Features are Missing
The robustness properties of the approach are demonstrated on both real and synthetic data.
Reliable Semi-Supervised Learning when Labels are Missing at Random
Semi-supervised learning methods are motivated by the availability of large datasets with unlabeled features in addition to labeled data.
Composite Gaussian Processes: Scalable Computation and Performance Analysis
Gaussian process (GP) models provide a powerful tool for prediction but are computationally prohibitive using large data sets.
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