Sleep stage classification constitutes an important preliminary exam in the diagnosis of sleep disorders. It is traditionally performed by a sleep expert who assigns to each 30s of signal a sleep stage, based on the visual inspection of signals such as electroencephalog... View more
 Aboalayon, K., Faezipour, M., Almuhammadi, W., and Moslehpour, S. Sleep Stage Classification Using EEG Signal Analysis: A Comprehensive Survey and New Investigation. Entropy 18, 9 (2016), 272.
 Allan Hobson, J. A manual of standardized terminology, techniques and scoring system for sleep stages of human subjects. Electroencephalography and Clinical Neurophysiology 26, 6 (June 1969), 644.
 Banko, M., and Brill, E. Scaling to very very large corpora for natural language disambiguation. In Proceedings of the 39th Annual Meeting on Association for Computational Linguistics (Stroudsburg, PA, USA, 2001), ACL '01, Association for Computational Linguistics, pp. 26-33.
 Bashivan, P., Rish, I., Yeasin, M., and Codella, N. Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networks. ICLR (2016), 1-15.
 Bergstra, J., D., Y., and D., C. D. Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures. ICML (2013).
 Berthomier, C., Drouot, X., Herman-Stoïca, M., Berthomier, P., Prado, J., Bokar-Thire, D., Benoit, O., Mattout, J., and D'Ortho, M.-P. Automatic analysis of single-channel sleep EEG: validation in healthy individuals. Sleep 30, 11 (2007), 1587-1595.
 Blankertz, B., Tomioka, R., Lemm, S., Kawanabe, M., and Muller, K. R. Optimizing spatial filters for robust EEG single-trial analysis. IEEE Signal Processing Magazine 25, 1 (2008), 41-56.
 Cecotti, H., and Gräser, A. Convolutional Neural Network with embedded Fourier Transform for EEG Classification. In 19th International Conference on Pattern Recognition (Dec 2008), pp. 1-4.
 Cecotti, H., and Gräser, A. Convolutional Neural Networks for P300 Detection with Application to Brain-Computer Interfaces. IEEE Trans. Pattern Anal. Mach. Intell. 33, 3 (Mar. 2011), 433-445.
 Chen, T., and Guestrin, C. XGBoost: A Scalable Tree Boosting System. In Proceedings of the 22nd International Conference on Knowledge Discovery and Data Mining (2016), ACM, pp. 785-794.