A new algorithm is presented for the automatic segmentation and classification of brain tissue from 3D MR scans. It uses discriminative Random Decision Forest classification and ta...
Zhao Yi, Antonio Criminisi, Jamie Shotton, Andr...
We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hid...
John D. Lafferty, Andrew McCallum, Fernando C. N. ...
This paper presents multi-conditional learning (MCL), a training criterion based on a product of multiple conditional likelihoods. When combining the traditional conditional proba...
Andrew McCallum, Chris Pal, Gregory Druck, Xuerui ...
Abstract--Recently, the following discrimination aware classification problem was introduced: given a labeled dataset and an attribute , find a classifier with high predictive accu...
We develop a semi-supervised learning method that constrains the posterior distribution of latent variables under a generative model to satisfy a rich set of feature expectation c...