Results 231 to 240 of about 89,316 (267)
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1991
In the previous chapters, we examined various methods which are applied directly to the likelihood or to the posterior density. In this and the following chapters, we examine the data augmentation algorithms, including the EM algorithm, the data augmentation algorithm and the Gibbs sampler.
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In the previous chapters, we examined various methods which are applied directly to the likelihood or to the posterior density. In this and the following chapters, we examine the data augmentation algorithms, including the EM algorithm, the data augmentation algorithm and the Gibbs sampler.
openaire +1 more source
Procrustes Alignment with the EM Algorithm
1999This paper casts the problem of point-set alignment via Procrustes analysis into a maximum likelihood framework using the EM algorithm. The aim is to improve the robustness of the Procrustes alignment to noise and clutter. By constructing a Gaussian mixture model over the missing correspondences between individual points, we show how alignment can be ...
Bin Luo 0001, Edwin R. Hancock
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PID-based search algorithm: A novel metaheuristic algorithm based on PID algorithm
Expert Systems With Applications, 2023Yuansheng Gao
exaly
The Whale Optimization Algorithm
Advances in Engineering Software, 2016Seyedali Mirjalili, Andrew Lewis
exaly
An efficient k-means clustering algorithm: analysis and implementation
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002N S Netanyahu
exaly
On the performance of artificial bee colony (ABC) algorithm
Applied Soft Computing Journal, 2008Dervis Karaboga
exaly