MAP Inference Via ℓ -Sphere Linear Program Reformulation

International Journal of Computer Vision, pp. 1913-1936, 2020.

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Abstract:

Maximum a posteriori (MAP) inference is an important task for graphical models. Due to complex dependencies among variables in realistic models, finding an exact solution for MAP inference is often intractable. Thus, many approximation methods have been developed, among which the linear programming (LP) relaxation based methods show promi...More

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