Nowadays, crowdsourcing has become an increasingly popular paradigm for large-scale
data collection, annotation, and classification. Today's rapid growth of crowdsourcing …

We consider a budgeted combinatorial multi-armed bandit setting where, in every round, the
algorithm selects a super-arm consisting of one or more arms. The goal is to minimize the …

Crowd-sourcing has attracted much attention due to its growing importance to society, and
numerous studies have been conducted on task allocation and wage determination. Recent …

In this paper, we investigate a Multi-Armed Bandit (MAB) setting where an arm exits the
game if the algorithm continuously neglects it. This setup is motivated by real-world …

In this paper, we analyze PAC learnability from labels produced by crowdsourcing. In our
setting, unlabeled examples are drawn from a distribution and labels are crowdsourced from …

Mobile crowdsourcing is a promising paradigm for collecting sensing data by leveraging
contributions of numerous mobile smart phones. It works efficiently with Word of Mouth Mode …

Significant disruption to the educational sector occurred due to the COVID-19 pandemic.
This shed a light on the need for new delivery methods and greater collaboration, which has …

This paper presents the first systematic investigation of the potential performance gains for
crowd work systems, deriving from available information at the requester about individual …

Task selection (picking an appropriate labeling task) and worker selection (assigning the
labeling task to a suitable worker) are two major challenges in task assignment for …

We study the effective use of crowdsourcing in filling missing values in a given relation (eg, a
table containing different attributes of celebrity stars, such as nationality and age). A task …