We propose a non-linear graphical model for structured prediction. It combines the power of deep neural networks to extract high level features with the graphical framework of Mar...
In this paper we present a system for automatically integrating unstructured text into a multi-relational database using state-of-the-art statistical models for structure extracti...
We propose a means of extending Conditional Random Field modeling to decision-theoretic planning where valuation is dependent upon fullyobservable factors. Representation is discu...
This work relates to the implementation of a 2D conditional random field model in the context of document image analysis. Our model makes it possible to take variability into acco...