2022
PGM
PGM 2022
Graphical Representations for Algebraic Constraints of Linear Structural Equations Models
Abstract
The observational characteristics of a linear structural equation model can be effectively described by polynomial constraints on the observed covariance matrix. However, these polynomials can be exponentially large, making them impractical for many purposes. In this paper, we present a graphical notation for many of these polynomial constraints. The expressive power of this notation is investigated both theoretically and empirically.
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Interdisciplinary Bridge
— Knowledge & Reasoning and Mathematics & Optimization
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Trend Setter
— Causal Inference
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Keyword Pioneer
— polynomial constraint
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Speech & Audio