Cross-Subject Transfer Learning Improves the Practicality of Real-World Applications of Brain-Computer Interfaces.
Kuan-Jung ChiangChun-Shu WeiMasaki NakanishiTzyy-Ping JungPublished in: NER (2019)
Keyphrases
- transfer learning
- brain computer interface
- real world
- knowledge transfer
- learning tasks
- labeled data
- cross domain
- active learning
- reinforcement learning
- eeg signals
- signal processing
- semi supervised learning
- evoked potentials
- machine learning
- domain adaptation
- multi task learning
- healthy subjects
- machine learning algorithms
- spinal cord injury
- transfer knowledge
- brain signals
- collaborative filtering
- text categorization
- text classification
- motor imagery
- learning algorithm
- manifold alignment
- target domain
- multi task
- transferring knowledge
- data sets
- cross domain learning
- neural network
- information retrieval
- decision trees
- feature space
- semi supervised
- text mining