Bayesian regression selecting valuable subset from mixed bag training data

Abstract

This paper addresses a problem in which we learn a regression model from sets of training data. Each of the sets has an only single label, and only one of the training data in the set reflects the label. This is particularly the case when the label is attached to a group of data, such as time-series data. The label is not attached to the point of the… (More)
DOI: 10.1109/ICPR.2016.7900024

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