Crowdsourced Classification with XOR Queries: Fundamental Limits and An Efficient Algorithm

31 Jan 2020 Daesung Kim Hye Won Chung

Crowdsourcing systems have emerged as an effective platform to label data and classify objects with relatively low cost by exploiting non-expert workers. To ensure reliable recovery of unknown labels with as few number of queries as possible, we consider an effective query type that asks "group attribute" of a chosen subset of objects... (read more)

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