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which is minimized to find the latent parameters.
Because the dimensionality of the latent parameters is too high to calculate directly.
On the other hand, in Table 1 the expectations for the latent parameters for identifying the outliers in the random walk RBDM are presented.
Specifically, we first obtain the object likelihoods in each image with saliency detection [17], and then estimate the latent parameters to update the object likelihoods.
Starting from initialization by saliency detection, the method alternates via updating the latent parameters, refining object segmentation and propagating appearance distribution among images.
Based on the graph model, our method successively updates the object likelihoods by the following iteration: (1) estimating the latent parameters and refining object segmentation, (2) transferring message among images and diffusing heat energy within individual image.
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θ k is the latent parameter set for the object model of I k.
c) estimate the latent parameter set θ k. d) acquire the updated object likelihoods L k ∗, 1 via guided filtering [16].
Like the original aspect model, the extended aspect model assumes conditional independence between word w j and document d k, that is, w j and d k are independent conditioned on the latent parameter z l and the context word : (8).
Step 4. Local object refinement (Section 4.1) a) let L k ∗, 3 = ( L k ∗, 0 + L k ∗, 1 + L k ∗, 2 ) / 3. b) re-estimate the latent parameter set θ k. c) acquire the updated object likelihoods L k ∗, 1 via guided filtering [16].
Within a ZIP likelihood framework, Long et al. (2014) proposed marginalized zero-inflated Poisson (MZIP) regression, which specifies a two-part model for counts with a set of regression coefficients for the marginal mean and, to complete model specification, a second set of regression coefficients for the latent parameter defining membership in the 'excess-zero' class.
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