Consistency of weighted majority votes

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22 Scopus citations

Abstract

We revisit from a statistical learning perspective the classical decision-theoretic problem of weighted expert voting. In particular, we examine the consistency (both asymptotic and finitary) of the optimal Nitzan-Paroush weighted majority and related rules. In the case of known expert competence levels, we give sharp error estimates for the optimal rule. When the competence levels are unknown, they must be empirically estimated. We provide frequentist and Bayesian analyses for this situation. Some of our proof techniques are non-standard and may be of independent interest. The bounds we derive are nearly optimal, and several challenging open problems are posed.

Original languageEnglish
Pages (from-to)3446-3454
Number of pages9
JournalAdvances in Neural Information Processing Systems
Volume4
Issue numberJanuary
StatePublished - 1 Jan 2014
Event28th Annual Conference on Neural Information Processing Systems 2014, NIPS 2014 - Montreal, Canada
Duration: 8 Dec 201413 Dec 2014

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Signal Processing

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