Transfer Learning: A Riemannian Geometry Framework With Applications to Brain–Computer Interfaces

OBJECTIVE: This paper tackles the problem of transfer learning in the context of electroencephalogram (EEG)-based brain-computer interface (BCI) classification. In particular, the problems of cross-session and cross-subject classification are considered. These problems concern the ability to use dat... View More