PCS-TL and HC-TL are new transfer learning methods that improve nonparametric Bayesian network learning under scarce data by avoiding negative transfer and using log-linear parameter pooling.
The sample complexity of learning fixed-structure Bayesian networks.Machine Learning, 29(2):165–180
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Transfer learning for nonparametric Bayesian networks
PCS-TL and HC-TL are new transfer learning methods that improve nonparametric Bayesian network learning under scarce data by avoiding negative transfer and using log-linear parameter pooling.