Equal Opportunity in Online Classification with Partial Feedback

NeurIPS 2019 Yahav BechavodKatrina LigettAaron RothBo WaggonerZhiwei Steven Wu

We study an online classification problem with partial feedback in which individuals arrive one at a time from a fixed but unknown distribution, and must be classified as positive or negative. Our algorithm only observes the true label of an individual if they are given a positive classification... (read more)

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