English(EN) Lifted Model Construction under Approximate Commutativity

新概念 {\epsilon}-交换性可实现近似提升模型构建

作者 PulseAugur 编辑部 · [1 个来源] · 2026-08-26 04:00

研究人员引入了一个名为 {\epsilon}-交换性的新概念，以解决提升模型构建中近似交换性的挑战。这种对精确交换性的放宽允许在从数据中学到的参数出现偏差时也能构建提升表示。所提出的方法通过实证证据证实，可确保实际适用性并以更短的运行时间保持准确的查询结果。 AI

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$新概念 {\epsilon}-交换性可实现近似提升模型构建$

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arXiv cs.AI TIER_1 English(EN) · Malte Luttermann, Jan Speller, Tanya Braun, Marcel Gehrke, Ralf M\"oller · 2026-08-26 04:00

近似交换律下的提升模型构造

arXiv:2608.24713v1 Announce Type: new Abstract: Lifted inference algorithms enable scalable probabilistic inference even for large object domains by leveraging the indistinguishability of objects in a probability distribution. An essential prerequisite for constructing a lifted r…