For many supervised learning problems, we possess prior knowledge about which features yield similar information about the target variable. In predicting the topic of a document, ...
Ted Sandler, John Blitzer, Partha Pratim Talukdar,...
Classifying pictures into one of several semantic categories is a classical image understanding problem. In this paper, we present a stratified approach to both binary (outdoor-in...
Statistical approaches to language learning typically focus on either short-range syntactic dependencies or long-range semantic dependencies between words. We present a generative...
Thomas L. Griffiths, Mark Steyvers, David M. Blei,...
Both human and automated tutors must infer what a student knows and plan future actions to maximize learning. Though substantial research has been done on tracking and modeling stu...
Anna N. Rafferty, Emma Brunskill, Thomas L. Griffi...
Abstract. In this study we propose a novel model for the representation of biological networks and provide algorithms for learning model parameters from experimental data. Our appr...