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Causal Learning via Manifold Regularization
This paper frames causal structure estimation as a machine learning task. The idea is to treat indicators of causal relationships between variables as ‘labels’ and to exploit available data on the variables of interest to provide features for the labelling task. Background scientific knowledge or an...
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| Pubblicato in: | J Mach Learn Res |
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| Autori principali: | , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2019
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6986916/ https://ncbi.nlm.nih.gov/pubmed/31992961 |
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