Domain Adaptation as a Problem of Inference on Graphical Models.
Kun ZhangMingming GongPetar StojanovBiwei HuangQingsong LiuClark GlymourPublished in: NeurIPS (2020)
Keyphrases
- graphical models
- domain adaptation
- probabilistic inference
- exact inference
- map inference
- belief networks
- factor graphs
- undirected graphical models
- belief propagation
- bayesian networks
- probabilistic model
- loopy belief propagation
- efficient inference algorithms
- approximate inference
- random variables
- probabilistic graphical models
- multiple sources
- statistical relational learning
- directed graphical models
- labeled data
- cross domain
- conditional random fields
- semi supervised
- markov networks
- possibilistic networks
- relational dependency networks
- markov logic networks
- semi supervised learning
- transfer learning
- sentiment classification
- bayesian inference
- test data
- data sets
- target domain
- document classification
- unlabeled data
- generative model
- text classification
- reinforcement learning