In this paper we extend PeerNomination, the most accurate peer reviewing algorithm to date, into WeightedPeerNomination . We show analytically that a weighting scheme can improve the overall accuracy of the selection significantly . We explicitly formulate assessors’ reliability weights in a way that doesn’t violate strategyproofness, and use this information to reweight their scores . We also implement several instances of reweighting methods and show empirically that our methods are robust in the face of noisy assessments. Finally, we implement severalinstances of reweightsing methods, and show empirical¬†emphasize¬†that our methods can improve overall accuracy in the selection of winners for peer-reviewed grants or prizes . Back to Mail Online home. Back to the page you came from .

Author(s) : Omer Lev, Nicholas Mattei, Paolo Turrini, Stanislav Zhydkov

Links : PDF - Abstract

Code :
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Keywords : methods - selection - peer - show - noisy -

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