Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...
We propose an approach to include contextual features for labeling images, in which each pixel is assigned to one of a finite set of labels. The features are incorporated into a p...
We describe a machine-learning-based approach for extracting attribute labels from Web form interfaces. Having these labels is a requirement for several techniques that attempt to ...
A bipartite query-URL graph, where an edge indicates that a document was clicked for a query, is a useful construct for finding groups of related queries and URLs. Here we use thi...
We develop a machine-learned similarity metric for Windows failure reports using telemetry data gathered from clients describing the failures. The key feature is a tuned callstack...
Kevin Bartz, Jack W. Stokes, John C. Platt, Ryan K...