Crowdsourcing refers to solving large problems by involving human workers that solve
component sub-problems or tasks. In data crowdsourcing, the problem involves data …

We consider a crowdsourcing database system that may cleanse, populate, or filter its data
by using human workers. Just like a conventional DB system, such a crowdsourcing DB …

Crowdsourcing and human computation enable organizations to accomplish tasks that are
currently not possible for fully automated techniques to complete, or require more flexibility …

Given a set V of n elements we wish to linearly order them given pairwise preference labels
which may be non-transitive (due to irrationality or arbitrary noise). The goal is to linearly …

Our work investigates the problem of retrieving the maximum item from a set in
crowdsourcing environments. We first develop parameterized families of max algorithms …

Abstract We consider $(\epsilon,\delta) $-PAC maximum-selection and ranking using
pairwise comparisons for general probabilistic models whose comparison probabilities …

Hypothesis selection is a fundamental problem in learning theory and statistics. Given a
dataset and a finite set of candidate distributions, the goal is to select a distribution that …

We consider the problem of maximizing a monotone submodular function under noise.
Since the 1970s there has been a great deal of work on optimization of submodular …

We study the problem of designing a mechanism to rank items in forums by making use of
the user reviews such as thumb and star ratings. We compare mechanisms where forum …

PAC maximum selection (maxing) and ranking of $ n $ elements via random pairwise
comparisons have diverse applications and have been studied under many models and …