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Learning equivalence classes of directed acyclic latent variable models from multiple datasets with overlapping variables, incl. discussion by Ricardo Silva
Ricardo Silva , Robert E. Tillman
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Oznake: computer science;machine learning;graphical models
While there has been considerable research in learning probabilistic graphical models from data for predictive and causal inference, almost all existing algorithms assume a single dataset of i.i.d. observations for all variables. For many applications, it may be impossible or impractical to obtain s ...
Leto: 2011 Vir: videolectures.net
When causality matters for prediction:Investigating the practical tradeoffs
Robert E. Tillman , Peter Spirtes
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Oznake: computer science;machine learning;graphical models
Leto: 2008 Vir: videolectures.net
Št. zadetkov: 2
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