Domain Adaptation As a Problem of Inference on Graphical Models.
Kun ZhangMingming GongPetar StojanovBiwei HuangClark GlymourPublished in: CoRR (2020)
Keyphrases
- graphical models
- domain adaptation
- probabilistic inference
- exact inference
- map inference
- bayesian networks
- belief networks
- belief propagation
- undirected graphical models
- efficient inference algorithms
- factor graphs
- loopy belief propagation
- approximate inference
- probabilistic graphical models
- random variables
- probabilistic model
- cross domain
- directed graphical models
- multiple sources
- conditional random fields
- labeled data
- semi supervised
- relational dependency networks
- possibilistic networks
- sentiment classification
- markov networks
- test data
- semi supervised learning
- transfer learning
- statistical relational learning
- unlabeled data
- document classification
- markov logic networks
- graph cuts
- markov random field
- training set
- co training
- bayesian inference
- supervised learning
- reinforcement learning
- machine learning