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An efficient inference in meanfield approximation by adaptive manifold filtering: (Machine learning & data mining)
, Article Proceedings of the 4th International Conference on Computer and Knowledge Engineering, ICCKE 2014 ; 2014 , p. 581-585 ; Ramezanpur, S ; Kasaei, S ; Sanaei, E ; Sharif University of Technology
Abstract
A new method for speeding up the approximate maximum posterior marginal (MPM) inference in meanfield approximation of a fully connected graph is introduced. Weight of graph edges is measured by mixture of Gaussian kernels. This fully connected graph is used for segmentation of image data. The bottleneck of the inference in meanfield approximation is where the similar bilateral filtering is needed for updating the marginal in the message passing step. To speed up the inference, the adaptive manifold high dimensional Gaussian filter is used. As its time complexity is 0(ND), it leads to accelerating the marginal update in the message passing step. Its time complexity is linear and relative to...