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Tractable nonparametric Bayesian inference in Poisson proce..:

, In: Proceedings of the 26th Annual International Conference on Machine Learning,

Adams, Ryan Prescott ; Murray, Iain ; MacKay, David J. C. - p. 9-16 , 2009

Link: https://dl.acm.org/doi/10.1145/1553374.1553376

RT 
T1 <cTitle>Proceedings of the 26th Annual International Conference on Machine Learning</cTitle>: T1 <Title>Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-1553376&Exemplar=1&LAN=DE
				
A1 Adams, Ryan Prescott
A1 Murray, Iain
A1 MacKay, David J. C.
PB ACM
YR 2009
K1 Theory of computation
K1 Theory and algorithms for application domains
K1 Machine learning theory
K1 Inductive inference
K1 Computing methodologies
K1 Modeling and simulation
K1 Model development and analysis
K1 Model verification and validation
K1 Markov decision processes
K1 Mathematics of computing
K1 Probability and statistics
K1 Probabilistic reasoning algorithms
K1 Markov-chain Monte Carlo methods
K1 Probabilistic representations
K1 Markov networks
K1 Nonparametric statistics
K1 Sequential Monte Carlo methods
K1 Probabilistic algorithms
K1 Modeling methodologies
K1 Stochastic processes
K1 Markov processes
SP 9
OP 16
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/1553374.1553376
DO https://dl.acm.org/doi/10.1145/1553374.1553376
SF ELIB - SuUB Bremen

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