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Dec, 2017
学习独立的因果机制
Learning Independent Causal Mechanisms
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Giambattista Parascandolo, Mateo Rojas-Carulla, Niki Kilbertus, Bernhard Schölkopf
TL;DR
通过模拟物理机制，我们开发出一种无监督学习的算法，能够从变换后的数据点中恢复出一组相互独立的机制，并且这些机制可以移植到新的领域中，对于迁移学习有重要的启示和应用。
Abstract
Independent causal
mechanisms
are a central concept in the study of causality with implications for machine learning tasks. In this work we develop an algorithm to recover a set of (inverse) independent
mechanisms
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