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» Hardware-Efficient Belief Propagation
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ICPR
2006
IEEE
16 years 25 days ago
Finding Text in Natural Scenes by Figure-Ground Segmentation
Much past research on finding text in natural scenes uses bottom-up grouping processes to detect candidate text features as a first processing step. While such grouping procedures...
Huiying Shen, James Coughlan
ICML
2006
IEEE
16 years 17 days ago
Probabilistic inference for solving discrete and continuous state Markov Decision Processes
Inference in Markov Decision Processes has recently received interest as a means to infer goals of an observed action, policy recognition, and also as a tool to compute policies. ...
Marc Toussaint, Amos J. Storkey
ICML
2004
IEEE
16 years 17 days ago
Variational methods for the Dirichlet process
Variational inference methods, including mean field methods and loopy belief propagation, have been widely used for approximate probabilistic inference in graphical models. While ...
David M. Blei, Michael I. Jordan
ICML
2004
IEEE
16 years 17 days ago
Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data
In sequence modeling, we often wish to represent complex interaction between labels, such as when performing multiple, cascaded labeling tasks on the same sequence, or when longra...
Charles A. Sutton, Khashayar Rohanimanesh, Andrew ...
ICML
2004
IEEE
16 years 17 days ago
Approximate inference by Markov chains on union spaces
A standard method for approximating averages in probabilistic models is to construct a Markov chain in the product space of the random variables with the desired equilibrium distr...
Max Welling, Michal Rosen-Zvi, Yee Whye Teh