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A Tight Convex Upper Bound on the Likelihood of a Finite Mixture
The likelihood function of a finite mixture model is a non-convex function with multiple local maxima and commonly used iterative algorithms such as EM will converge to different solutions depending on initial conditions.
Tighter Linear Program Relaxations for High Order Graphical Models
In this work, we study the LP relaxations that result from enforcing additional consistency constraints between the HOP and the rest of the model.
Learning about Canonical Views from Internet Image Collections
Our results clearly show that the most likely view in the search engine corresponds to the same view preferred by human subjects in experiments.
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