Learning in Confusion: Batch Active Learning with Noisy Oracle

27 Sep 2019Gaurav GuptaAnit Kumar SahuWan-Yi Lin

We study the problem of training machine learning models incrementally using active learning with access to imperfect or noisy oracles. We specifically consider the setting of batch active learning, in which multiple samples are selected as opposed to a single sample as in classical settings so as to reduce the training overhead... (read more)

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