Search Results for author: Reshef Meir

Found 7 papers, 1 papers with code

Efficient Online Crowdsourcing with Complex Annotations

no code implementations25 Jan 2024 Reshef Meir, Viet-An Nguyen, Xu Chen, Jagdish Ramakrishnan, Udi Weinsberg

Crowdsourcing platforms use various truth discovery algorithms to aggregate annotations from multiple labelers.

Empirical Bayes approach to Truth Discovery problems

no code implementations9 Jun 2022 Tsviel Ben Shabat, Reshef Meir, David Azriel

When aggregating information from conflicting sources, one's goal is to find the truth.

Strategyproof Facility Location Mechanisms on Discrete Trees

no code implementations4 Feb 2021 Alina Filimonov, Reshef Meir

Our main result is a full characterization of onto and SP mechanisms.

Computer Science and Game Theory

Representative Committees of Peers

no code implementations14 Jun 2020 Reshef Meir, Fedor Sandomirskiy, Moshe Tennenholtz

We show that a k-sortition (a random committee of k voters with the majority vote within the committee) leads to an outcome within the factor 1+O(1/k) of the optimal social cost for any number of voters n, any number of issues $m$, and any preference profile.

Bidding in Spades

1 code implementation24 Dec 2019 Gal Cohensius, Reshef Meir, Nadav Oved, Roni Stern

We present a Spades bidding algorithm that is superior to recreational human players and to publicly available bots.

Frustratingly Easy Truth Discovery

no code implementations2 May 2019 Reshef Meir, Ofra Amir, Omer Ben-Porat, Tsviel Ben-Shabat, Gal Cohensius, Lirong Xia

Truth discovery is a general name for a broad range of statistical methods aimed to extract the correct answers to questions, based on multiple answers coming from noisy sources.

On Sex, Evolution, and the Multiplicative Weights Update Algorithm

no code implementations17 Feb 2015 Reshef Meir, David Parkes

We show that the marginal allele distributions induced by the population dynamics precisely match the marginals induced by a multiplicative weights update algorithm in this general setting, thereby affirming and substantially generalizing these earlier results.

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