Transfer learning extensions for the probabilistic classification vector machine.
Christoph RaabFrank-Michael SchleifPublished in: Neurocomputing (2020)
Keyphrases
- transfer learning
- text classification
- cross domain learning
- machine learning
- knowledge transfer
- cross domain
- labeled data
- learning tasks
- support vector
- cross domain text classification
- machine learning algorithms
- structure learning
- document classification
- generative model
- support vector machine
- databases
- domain adaptation
- decision trees
- reinforcement learning
- text categorization
- semi supervised learning
- feature space
- multi task
- feature vectors
- text mining
- collaborative filtering
- multi task learning
- label information
- manifold alignment
- neural network
- probabilistic model
- bayesian networks
- graphical models
- learning algorithm
- transfer knowledge