Active Learning with Importance Sampling

10 Oct 2019Muni Sreenivas PydiVishnu Suresh Lokhande

We consider an active learning setting where the algorithm has access to a large pool of unlabeled data and a small pool of labeled data. In each iteration, the algorithm chooses few unlabeled data points and obtains their labels from an oracle... (read more)

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