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The Ethereal
Causality for Machine Learning
November 24, 2019 ยท Declared Dead ยท ๐ Probabilistic and Causal Inference
"No code URL or promise found in abstract"
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Authors
Bernhard Schรถlkopf
arXiv ID
1911.10500
Category
cs.LG: Machine Learning
Cross-listed
cs.AI,
stat.ML
Citations
526
Venue
Probabilistic and Causal Inference
Last Checked
3 months ago
Abstract
Graphical causal inference as pioneered by Judea Pearl arose from research on artificial intelligence (AI), and for a long time had little connection to the field of machine learning. This article discusses where links have been and should be established, introducing key concepts along the way. It argues that the hard open problems of machine learning and AI are intrinsically related to causality, and explains how the field is beginning to understand them.
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