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Behind Distribution Shift: Mining Driving Forces of Changes and Causal Arrows
We address two important issues in causal discovery from nonstationary or heterogeneous data, where parameters associated with a causal structure may change over time or across data sets. First, we investigate how to efficiently estimate the “driving force” of the nonstationarity of a causal mechani...
Uloženo v:
| Vydáno v: | Proc IEEE Int Conf Data Min |
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| Hlavní autoři: | , , , , , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
2017
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6502242/ https://ncbi.nlm.nih.gov/pubmed/31068766 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/ICDM.2017.114 |
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