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原文連結
論文資訊
- 類型:已發表論文
- 日期:2014-04-04
摘要
The introduction of the partial 資訊 decomposition generated a flurry of proposals for defining an intersection 資訊 that quantifies how much of "the same 資訊" two or more random variables specify about a target random variable. As of yet, none is wholly satisfactory. A palatable measure of intersection 資訊 would provide a principled way to quantify slippery concepts, such as synergy. Here, we introduce an intersection 資訊 measure based on the Gacs-Korner common random variable that is the first to satisfy the coveted target monotonicity property. Our measure is imperfect, too, and we suggest directions for improvement.
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