Bayesian multi-task learning for common spatial patterns

Proceedings - International Workshop on Pattern Recognition in NeuroImaging, PRNI 2011

Volumn , Issue , 2011, Pages 61-64

  Kang, Hyohyeong ^a   Choi, Seungjin ^a  

^a Pohang University of Science and Technology (POSTECH)   (South Korea)

Author keywords

Bayesian multi task learning; Brain computer interface; Common spatial patterns

Indexed keywords

CLASSIFICATION PERFORMANCE; COMMON SPATIAL PATTERNS; DATA SETS; FEATURE EXTRACTION METHODS; GAUSSIANS; LINEAR GENERATIVE MODEL; MULTITASK LEARNING; NUMERICAL EXPERIMENTS; PRECISION PARAMETER; PROBABILISTIC MODELS; TRAINING SAMPLE;

BRAIN MODELS; CLASSIFICATION (OF INFORMATION); ELECTROENCEPHALOGRAPHY; FEATURE EXTRACTION; INTERFACES (COMPUTER); NUMERICAL METHODS; PRASEODYMIUM ALLOYS; SAMPLING;

BRAIN COMPUTER INTERFACE;

EID: 80051959443     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/PRNI.2011.8     Document Type: Conference Paper

References (6)

1. A. Cichocki, Y. Washizawa, T. Rutkowski, H. Bakardjian, A. H. Phan, S. Choi, H. Lee, Q. Zhao, L. Zhang, and Y. Li, "Noninvasive BCIs: Multiway signal-processing array decompositions," IEEE Computer, vol. 41, no. 10, pp. 34-42, 2008.
2. T. Heskes, "Empirical Bayes for learning to learn," in Proceedings of the International Conference on Machine Learning (ICML), San Francisco, CA, 2000.
3. H. Kang, Y. Nam, and S. Choi, "Composite common spatial pattern for subject-to-subject transfer," IEEE Signal Processing Letters, vol. 16, no. 8, pp. 683-686, 2009.
4. Z. J. Koles, "The quantitative extraction and topographic mapping of the abnormal components," EEG and Clinical Neurophysilology, vol. 79, pp. 440-447, 1991.
5. F. Lotte and G. Cuntai, "Learning from other subjects helps reducing brain-computer interface calibration time," in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Dallas, TX, 2010.
6. W. Wu, Z. Chen, S. Gao, and E. N. Brown, "A probabilistic framework for learning robust common spatial patterns," in Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Minneapolis, MN, 2009.