957 citations · 1.3k across the 29 of their papers we have counts for
5 papers · 1 filter
Learning with Scope, with Application to Information Extraction and Classification
David Blei, J Andrew Bagnell, Andrew McCallum
In probabilistic approaches to classification and information extraction, one typically builds a statistical model of words under the assumption that future data will exhibit the s…
The Issue-Adjusted Ideal Point Model
Sean M. Gerrish, David M. Blei
We develop a model of issue-specific voting behavior. This model can be used to explore lawmakers' personal voting patterns of voting by issue area, providing an exploratory window…
A Bayesian Nonparametric Approach to Image Super-resolution
Gungor Polatkan, Mingyuan Zhou, Lawrence Carin +2
Super-resolution methods form high-resolution images from low-resolution images. In this paper, we develop a new Bayesian nonparametric model for super-resolution. Our method uses…
A Bayesian Boosting Model
Alexander Lorbert, David M. Blei, Robert E. Schapire +1
We offer a novel view of AdaBoost in a statistical setting. We propose a Bayesian model for binary classification in which label noise is modeled hierarchically. Using variational…
Variational Inference in Nonconjugate Models
Chong Wang, David M. Blei
Mean-field variational methods are widely used for approximate posterior inference in many probabilistic models. In a typical application, mean-field methods approximately compute…