摘要翻译：
我们开发了几个算法，利用了两种常见的方法来限定图形模型中的MPE查询：小桶消除和线性规划松弛的消息传递更新。这两种方法非常相似，并为另一种方法提供了有用的视角；我们的混合方法试图平衡每种方法的优势。我们通过大量的经验评估证明了我们的混合算法的能力。最值得注意的是，由我们的一个新算法计算的启发式函数引导的分支定界搜索最近在PASCAL2推理挑战赛中获得了第一名。
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英文标题：
《Join-graph based cost-shifting schemes》
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作者：
Alexander T. Ihler, Natalia Flerova, Rina Dechter, Lars Otten
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最新提交年份：
2012
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
  We develop several algorithms taking advantage of two common approaches for bounding MPE queries in graphical models: minibucket elimination and message-passing updates for linear programming relaxations. Both methods are quite similar, and offer useful perspectives for the other; our hybrid approaches attempt to balance the advantages of each. We demonstrate the power of our hybrid algorithms through extensive empirical evaluation. Most notably, a Branch and Bound search guided by the heuristic function calculated by one of our new algorithms has recently won first place in the PASCAL2 inference challenge.
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PDF链接：
https://arxiv.org/pdf/1210.4878