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NIPS
2008
13 years 9 months ago
Efficient Sampling for Gaussian Process Inference using Control Variables
Sampling functions in Gaussian process (GP) models is challenging because of the highly correlated posterior distribution. We describe an efficient Markov chain Monte Carlo algori...
Michalis Titsias, Neil D. Lawrence, Magnus Rattray
CORR
2010
Springer
126views Education» more  CORR 2010»
13 years 4 months ago
From Pathwidth to Connected Pathwidth
It is proven that the connected pathwidth of any graph G is at most 2
Dariusz Dereniowski
UAI
2008
13 years 9 months ago
Convergent Message-Passing Algorithms for Inference over General Graphs with Convex Free Energies
Inference problems in graphical models can be represented as a constrained optimization of a free energy function. It is known that when the Bethe free energy is used, the fixedpo...
Tamir Hazan, Amnon Shashua
ECAI
2010
Springer
13 years 8 months ago
The Necessity of Bounded Treewidth for Efficient Inference in Bayesian Networks
Abstract. Algorithms for probabilistic inference in Bayesian networks are known to have running times that are worst-case exponential in the size of the network. For networks with ...
Johan Kwisthout, Hans L. Bodlaender, Linda C. van ...
AAAI
2010
13 years 9 months ago
Efficient Lifting for Online Probabilistic Inference
Lifting can greatly reduce the cost of inference on firstorder probabilistic graphical models, but constructing the lifted network can itself be quite costly. In online applicatio...
Aniruddh Nath, Pedro Domingos