Crowdsourcing enables one to leverage on the intelligence and wisdom of potentially large
groups of individuals toward solving problems. Common problems approached with …

It is well known that apps running on mobile devices extensively track and leak users'
personally identifiable information (PII); however, these users have little visibility into PII …

Learning-from-crowds aims to design proper aggregation strategies to infer the unknown
true labels from the noisy labels provided by ordinary web workers. This paper presents max …

Swarm intelligence has become a hot research field of artificial intelligence. Considering the
importance of swarm intelligence for the future development of artificial intelligence, we …

With the proliferation of sensor-rich mobile devices, crowd sensing has emerged as a new
paradigm of collecting information from the physical world. However, the sensory data …

Crowdsourcing has gained immense popularity in machine learning applications for
obtaining large amounts of labeled data. Crowdsourcing is cheap and fast, but suffers from …

In order to effectively infer correct labels from noisy crowdsourced annotations, learning-from-
crowds models have introduced expert validation. However, little research has been done …

Crowdsourcing is a paradigm that provides a cost-effective solution for obtaining services or
data from a large group of users. It is increasingly being used in modern society for data …

As an effective way to solicit useful information from the crowd, crowdsourcing has emerged
as a popular paradigm to solve challenging tasks. However, the data provided by the …

With the increasing complexity of tasks that are crowdsourced, requesters need to form
teams of professional workers that can satisfy complex task skill requirements. Team …