New data-driven approaches to improve probabilistic model structure learning
To learn the network structures used in probabilistic models (e.g., Bayesian network), many researchers proposed structure learning algorithms to extract the network structure from data. However, structure learning is a challenging problem due to the extremely large number of possible structure cand...
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| Format: | Thesis |
| Language: | English |
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2019
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| Online Access: | https://hdl.handle.net/10356/84123 http://hdl.handle.net/10220/50443 |