Add to ORKGWe present the first model of optimal voting under adversar-ial noise. From this viewpoint, voting rules are seen as error-correcting codes: their goal is to correct errors in the input rankings and recover a ranking that is close to the ground truth. We derive worst-case bounds on the relation between the average accuracy of the input votes, and the accuracy of the output ranking. Empirical results from real data show that our approach produces significantly more accurate rankings than alternative approaches
Modern social choice theory, following Kenneth Arrow, treats voting as a method for aggregating dive...
AbstractScoring rules and voting trees are two broad and concisely-representable classes of voting r...
We present an improved bound on the difference between training and test errors for voting classifie...
We present the first model of optimal voting under adversarial noise. From this viewpoint, voting ru...
A well-studied approach to the design of voting rules views them as maximum likelihood estimators; g...
A well-studied approach to the design of voting rules views them as maximum likelihood estimators; g...
Voting is a very general method of preference aggregation. A voting rule takes as input every voter'...
Voting is a very general method of preference aggregation. A voting rule takes as input ev-ery voter...
Motivated by applications to crowdsourcing, we study voting rules that output a correct ranking of a...
Motivated by applications to crowdsourcing, we study voting rules that output a correct ranking of a...
Rank aggregation is the problem of generating an overall ranking from a set of individual votes whic...
When election reforms such as Ranked Choice Voting or the Alternative Vote are proposed to replace p...
In an election held in a noisy environment, agents may unintentionally perturb the outcome by commun...
We explore the relationship between two approaches to rationalizing voting rules: the maximum likeli...
While impossibility results have established that no perfect voting rules exist, efficiently designi...
Modern social choice theory, following Kenneth Arrow, treats voting as a method for aggregating dive...
AbstractScoring rules and voting trees are two broad and concisely-representable classes of voting r...
We present an improved bound on the difference between training and test errors for voting classifie...
We present the first model of optimal voting under adversarial noise. From this viewpoint, voting ru...
A well-studied approach to the design of voting rules views them as maximum likelihood estimators; g...
A well-studied approach to the design of voting rules views them as maximum likelihood estimators; g...
Voting is a very general method of preference aggregation. A voting rule takes as input every voter'...
Voting is a very general method of preference aggregation. A voting rule takes as input ev-ery voter...
Motivated by applications to crowdsourcing, we study voting rules that output a correct ranking of a...
Motivated by applications to crowdsourcing, we study voting rules that output a correct ranking of a...
Rank aggregation is the problem of generating an overall ranking from a set of individual votes whic...
When election reforms such as Ranked Choice Voting or the Alternative Vote are proposed to replace p...
In an election held in a noisy environment, agents may unintentionally perturb the outcome by commun...
We explore the relationship between two approaches to rationalizing voting rules: the maximum likeli...
While impossibility results have established that no perfect voting rules exist, efficiently designi...
Modern social choice theory, following Kenneth Arrow, treats voting as a method for aggregating dive...
AbstractScoring rules and voting trees are two broad and concisely-representable classes of voting r...
We present an improved bound on the difference between training and test errors for voting classifie...