Solving Marginal MAP Problems with NP Oracles and Parity Constraints

作者: Yexiang Xue, Zhiyuan Li, Stefano Ermon, Carla P Gomes, Bart Selman

摘要

Arising from many applications at the intersection of decision-making and machine learning, Marginal Maximum A Posteriori (Marginal MAP) problems unify the two main classes of inference, namely maximization (optimization) and marginal inference (counting), and are believed to have higher complexity than both of them. We propose XOR

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