灰心丧气
发表于 2025-3-25 06:53:25
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玉米
发表于 2025-3-25 11:28:38
Inference,lways answer probabilistic queries using standard Markov network inference methods on the instantiated network. However, due to the size and complexity of the resulting network, this is often infeasible. Instead, the methods we discuss here combine probabilistic methods with ideas from logical infer
高原
发表于 2025-3-25 14:45:36
Learning,anually specifying the complete model. We begin by discussing weight learning, in which we try to find the formula weights that maximize the likelihood or conditional likelihood of a relational database. Our methods for solving this problem are based on convex optimization but take into account the
lobster
发表于 2025-3-25 19:13:27
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blight
发表于 2025-3-25 23:09:10
Applications,cover eight applications: collective classification, social network analysis, entity resolution, information extraction, coreference resolution, robot mapping, link-based clustering, and semantic network extraction.
Calibrate
发表于 2025-3-26 01:33:00
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Discrete
发表于 2025-3-26 05:43:22
8楼
Precursor
发表于 2025-3-26 12:22:06
8楼
方便
发表于 2025-3-26 16:26:25
8楼
保存
发表于 2025-3-26 17:03:46
8楼