We explore the problem of assigning heterogeneous tasks to workers with different, unknown skill sets in crowdsourcing markets such as Amazon Mechanical Turk. We first formalize ...
The flourishing of online labor markets such as Amazon Mechanical Turk (MTurk) makes it easy to recruit many workers for solving small tasks. We study whether information elicita...
Thomas Pfeiffer, Xi Alice Gao, Yiling Chen, Andrew...
We examine designs for crowdsourcing contests, where participants compete for rewards given to superior solutions of a task. We theoretically analyze tradeoffs between the expecta...
Xi Alice Gao, Yoram Bachrach, Peter Key, Thore Gra...
Crowdsourcing has recently become popular among machine learning researchers and social scientists as an effective way to collect large-scale experimental data from distributed w...
While there are a number of subjectivity lexicons available for research purposes, none can be used commercially. We describe the process of constructing subjectivity lexicon(s) fo...
Accurate prediction of demographic attributes from social media and other informal online content is valuable for marketing, personalization, and legal investigation. This paper d...
John D. Burger, John C. Henderson, George Kim, Gui...
While a large body of research on image-based authentication has focused on memorability, comparatively less attention has been paid to the new security challenges these schemes m...
The task of 2-D articulated human pose estimation in natural images is extremely challenging due to the high level of variation in human appearance. These variations arise from di...
We explore how to improve machine translation systems by adding more translation data in situations where we already have substantial resources. The main challenge is how to buck ...
The explosion of image data on the Internet has the potential to foster more sophisticated and robust models and algorithms to index, retrieve, organize and interact with images a...
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai...