926 search results - page 44 / 186 » Outliers and Bayesian Inference |
NIPS
2007
15 years 1 days ago
2007
Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...
122
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ESOP
2011
Springer
14 years 2 months ago
2011
Springer
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
102
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AIIA
2003
Springer
15 years 3 months ago
2003
Springer
A bayesian network is an appropriate tool for working with uncertainty and probability, that are typical of real-life applications. In literature we find different approaches for b...
80
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IROS
2007
IEEE
15 years 4 months ago
2007
IEEE
Abstract— Real-world robotic environments are highly structured. The scalability of planning and reasoning methods to cope with complex problems in such environments crucially de...
ICONIP
2007
15 years 1 days ago
2007
Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially ...