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ICML
2004
IEEE
15 years 10 months ago
Relational sequential inference with reliable observations
We present a trainable sequential-inference technique for processes with large state and observation spaces and relational structure. Our method assumes "reliable observation...
Alan Fern, Robert Givan
ICAC
2006
IEEE
15 years 3 months ago
Learning Application Models for Utility Resource Planning
Abstract— Shared computing utilities allocate compute, network, and storage resources to competing applications on demand. An awareness of the demands and behaviors of the hosted...
Piyush Shivam, Shivnath Babu, Jeffrey S. Chase
UAI
2008
14 years 11 months ago
Learning Arithmetic Circuits
Graphical models are usually learned without regard to the cost of doing inference with them. As a result, even if a good model is learned, it may perform poorly at prediction, be...
Daniel Lowd, Pedro Domingos
ICML
2009
IEEE
15 years 10 months ago
Bayesian inference for Plackett-Luce ranking models
This paper gives an efficient Bayesian method for inferring the parameters of a PlackettLuce ranking model. Such models are parameterised distributions over rankings of a finite s...
John Guiver, Edward Snelson
ECML
2007
Springer
15 years 3 months ago
Bayesian Inference for Sparse Generalized Linear Models
We present a framework for efficient, accurate approximate Bayesian inference in generalized linear models (GLMs), based on the expectation propagation (EP) technique. The paramete...
Matthias Seeger, Sebastian Gerwinn, Matthias Bethg...