Search Results for author: Hideaki Imamura

Found 2 papers, 1 papers with code

Analysis of Minimax Error Rate for Crowdsourcing and Its Application to Worker Clustering Model

1 code implementation ICML 2018 Hideaki Imamura, Issei Sato, Masashi Sugiyama

In this paper, we derive a minimax error rate under more practical setting for a broader class of crowdsourcing models including the DS model as a special case.

Clustering

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