113 citations · 342 across the 17 of their papers we have counts for
5 papers · 1 filter
Deceptiveness of internet data for disease surveillance
Reid Priedhorsky, Dave Osthus, Ashlynn R. Daughton +2
Quantifying how many people are or will be sick, and where, is a critical ingredient in reducing the burden of disease because it helps the public health system plan and implement…
Co-training for Demographic Classification Using Deep Learning from Label Proportions
Ehsan Mohammady Ardehaly, Aron Culotta
Deep learning algorithms have recently produced state-of-the-art accuracy in many classification tasks, but this success is typically dependent on access to many annotated training…
Mining the Demographics of Political Sentiment from Twitter Using Learning from Label Proportions
Ehsan Mohammady Ardehaly, Aron Culotta
Opinion mining and demographic attribute inference have many applications in social science. In this paper, we propose models to infer daily joint probabilities of multiple latent…
Controlling for Unobserved Confounds in Classification Using Correlational Constraints
Virgile Landeiro, Aron Culotta
As statistical classifiers become integrated into real-world applications, it is important to consider not only their accuracy but also their robustness to changes in the data dist…
Identifying leading indicators of product recalls from online reviews using positive unlabeled learning and domain adaptation
Shreesh Kumara Bhat, Aron Culotta
Consumer protection agencies are charged with safeguarding the public from hazardous products, but the thousands of products under their jurisdiction make it challenging to identif…