{"type":"ScholarlyArticle","title":"Strategyproof Classification with Shared Inputs","authors":[{"name":"Reshef Meir","slug":"reshef-meir","given":"Reshef","family":"Meir","affiliation":""},{"name":"Ariel D. Procaccia","slug":"ariel-d-procaccia","given":"Ariel D.","family":"Procaccia","affiliation":""},{"name":"Jeffrey S. Rosenschein","slug":"jeffrey-s-rosenschein","given":"Jeffrey S.","family":"Rosenschein","affiliation":""}],"abstract":"Strategyproof classification deals with a setting where a decision-maker must classify a set of input points with binary labels, while minimizing the expected error. The labels of the input points are reported by self-interested agents, who might lie in order to obtain a classifier that more closely matches their own labels, thus creating a bias in the data; this motivates the design of truthful mechanisms that discourage false reports. Previous work [Meir et al., 2008] investigated both decision-theoretic and learning-theoretic variations of the setting, but only considered classifiers that belong to a degenerate class.In this paper we assume that the agents are interested in a shared set of input points. We show that this plausible assumption leads to powerful results. In particular, we demonstrate that variations of a truthful random dictator mechanism can guarantee approximately optimal outcomes with respect to any class of classifiers.Reshef Meir, Ariel D. Procaccia, Jeffrey S. Rosenschein","doi":null,"url":"https://ijcai.org/proceedings/2009/46","pdf":"https://ijcai.org/proceedings/2009/0046.pdf","markdown":"https://ijcai.org/proceedings/2009/46.md","bibtex":"https://ijcai.org/proceedings/2009/bibtex/46","volume":{"slug":"2009","title":"Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2009","url":"https://ijcai.org/proceedings/2009/","year":2009,"location":"Pasadena, California, USA","dates":"","editors":"Hiroaki Kitano","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":46,"pages":{"first":220,"last":224},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}