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Gaussian Conditional Random Fields for Classification
The extended method of local variational approximation of sigmoid function is used for solving empirical Bayes in GCRFBCb variant, whereas MAP value of latent variables is the basis for learning and inference in the GCRFBCnb variant.
Semi-supervised learning for structured regression on partially observed attributed graphs
We also show that the method can be useful for optimizing the costs of data collection in climate applications via active reduction of the number of weather stations to consider.
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