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UAI
2004
13 years 8 months ago
Exponential Families for Conditional Random Fields
In this paper we define conditional random fields in reproducing kernel Hilbert spaces and show connections to Gaussian Process classification. More specifically, we prove decompo...
Yasemin Altun, Alexander J. Smola, Thomas Hofmann
ACL
2009
13 years 4 months ago
Markov Random Topic Fields
Most approaches to topic modeling assume an independence between documents that is frequently violated. We present an topic model that makes use of one or more user-specified grap...
Hal Daume III
CVPR
2004
IEEE
14 years 8 months ago
Multiscale Conditional Random Fields for Image Labeling
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...
Miguel Á. Carreira-Perpiñán, ...
CSIE
2009
IEEE
14 years 1 months ago
Discriminative Random Fields for Behavior Modeling
This paper proposed an approach of human behavior modeling based on Discriminative Random Fields. In this model, by introducing the hidden behavior feature functions and time wind...
Tianyu Huang, Chongde Shi, Fengxia Li
CVPR
2007
IEEE
14 years 8 months ago
Learning Gaussian Conditional Random Fields for Low-Level Vision
Markov Random Field (MRF) models are a popular tool for vision and image processing. Gaussian MRF models are particularly convenient to work with because they can be implemented u...
Marshall F. Tappen, Ce Liu, Edward H. Adelson, Wil...