Riemannian Procrustes Analysis: Transfer Learning for Brain–Computer Interfaces
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Christian Jutten | Marco Congedo | Pedro Luiz Coelho Rodrigues | C. Jutten | M. Congedo | P. Rodrigues
[1] Levent Tunçel,et al. Optimization algorithms on matrix manifolds , 2009, Math. Comput..
[2] Jieyu Zhao,et al. Deep Neural Network with Joint Distribution Matching for Cross-Subject Motor Imagery Brain-Computer Interfaces , 2020, BioMed research international.
[3] N. Birbaumer,et al. BCI2000: a general-purpose brain-computer interface (BCI) system , 2004, IEEE Transactions on Biomedical Engineering.
[4] R. Bhatia. Positive Definite Matrices , 2007 .
[5] D. Zaykin,et al. Optimally weighted Z‐test is a powerful method for combining probabilities in meta‐analysis , 2011, Journal of evolutionary biology.
[6] Mehrtash Harandi,et al. Dimensionality Reduction on SPD Manifolds: The Emergence of Geometry-Aware Methods , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[7] Stéphane Lafon,et al. Diffusion maps , 2006 .
[8] Sung Chan Jun,et al. EEG datasets for motor imagery brain–computer interface , 2017, GigaScience.
[9] Nicolas Courty,et al. Optimal Transport for Domain Adaptation , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[10] Addison W. Bohannon,et al. Spectral Transfer Learning Using Information Geometry for a User-Independent Brain-Computer Interface , 2016, Front. Neurosci..
[11] Bernhard Schölkopf,et al. Transfer Learning in Brain-Computer Interfaces , 2015, IEEE Computational Intelligence Magazine.
[12] H. Shimodaira,et al. Improving predictive inference under covariate shift by weighting the log-likelihood function , 2000 .
[13] Marco Congedo,et al. EEG Source Analysis , 2013 .
[14] Christa Neuper,et al. Autocalibration and Recurrent Adaptation: Towards a Plug and Play Online ERD-BCI , 2012, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[15] Sridhar Mahadevan,et al. Manifold alignment using Procrustes analysis , 2008, ICML '08.
[16] Gernot R. Müller-Putz,et al. Random forests in non-invasive sensorimotor rhythm brain-computer interfaces: a practical and convenient non-linear classifier , 2016, Biomedizinische Technik. Biomedical engineering.
[17] Jonathan H. Manton,et al. Riemannian Gaussian Distributions on the Space of Symmetric Positive Definite Matrices , 2015, IEEE Transactions on Information Theory.
[18] Laurent Bougrain,et al. Median Nerve Stimulation Based BCI: A New Approach to Detect Intraoperative Awareness During General Anesthesia , 2019, Front. Neurosci..
[19] Niklas Koep,et al. Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation , 2016, J. Mach. Learn. Res..
[20] Innar Liiv,et al. Seriation and matrix reordering methods: An historical overview , 2010, Stat. Anal. Data Min..
[21] D. Kendall. A Survey of the Statistical Theory of Shape , 1989 .
[22] Klaus-Robert Müller,et al. Unsupervised Learning for Brain-Computer Interfaces Based on Event-Related Potentials: Review and Online Comparison [Research Frontier] , 2018, IEEE Computational Intelligence Magazine.
[23] Maureen Clerc,et al. Optimal transport Applied to Transfer Learning for P300 Detection , 2017, GBCIC.
[24] Motoaki Kawanabe,et al. Invariant Common Spatial Patterns: Alleviating Nonstationarities in Brain-Computer Interfacing , 2007, NIPS.
[25] Koby Crammer,et al. A theory of learning from different domains , 2010, Machine Learning.
[26] Ronald Phlypo,et al. Fixed Point Algorithms for Estimating Power Means of Positive Definite Matrices , 2016, IEEE Transactions on Signal Processing.
[27] Alexandre Barachant,et al. A Plug&Play P300 BCI Using Information Geometry , 2014, ArXiv.
[28] Christian Jutten,et al. " Brain Invaders": a prototype of an open-source P300-based video game working with the OpenViBE platform , 2011 .
[29] Vinay Jayaram,et al. MOABB: trustworthy algorithm benchmarking for BCIs , 2018, Journal of neural engineering.
[30] Alexandre Barachant,et al. Riemannian geometry for EEG-based brain-computer interfaces; a primer and a review , 2017 .
[31] M Congedo,et al. A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update , 2018, Journal of neural engineering.
[32] Christian Jutten,et al. Transfer Learning: A Riemannian Geometry Framework With Applications to Brain–Computer Interfaces , 2018, IEEE Transactions on Biomedical Engineering.
[33] S. Holm. A Simple Sequentially Rejective Multiple Test Procedure , 1979 .
[34] Moritz Grosse-Wentrup,et al. Beamforming in Noninvasive Brain–Computer Interfaces , 2009, IEEE Transactions on Biomedical Engineering.
[35] F. Yger,et al. Riemannian Approaches in Brain-Computer Interfaces: A Review , 2017, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[36] Emmanuel K. Kalunga,et al. Online SSVEP-based BCI using Riemannian geometry , 2015, Neurocomputing.
[37] Christian Jutten,et al. Multiclass Brain–Computer Interface Classification by Riemannian Geometry , 2012, IEEE Transactions on Biomedical Engineering.
[38] Ronen Talmon,et al. Parallel Transport on the Cone Manifold of SPD Matrices for Domain Adaptation , 2018, IEEE Transactions on Signal Processing.
[39] Klaus-Robert Müller,et al. Subject-independent mental state classification in single trials , 2009, Neural Networks.
[40] Ad Aertsen,et al. Review of the BCI Competition IV , 2012, Front. Neurosci..
[41] Alexandre Barachant,et al. A New Generation of Brain-Computer Interface Based on Riemannian Geometry , 2013, ArXiv.
[42] M. Congedo,et al. Procrustes problems in Riemannian manifolds of positive definite matrices , 2019, Linear Algebra and its Applications.
[43] Christian Jutten,et al. Multivariate Time-Series Analysis Via Manifold Learning , 2018, 2018 IEEE Statistical Signal Processing Workshop (SSP).
[44] Qiang Yang,et al. A Survey on Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.
[45] Ann B. Lee,et al. Diffusion maps and coarse-graining: a unified framework for dimensionality reduction, graph partitioning, and data set parameterization , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[46] M. Kawanabe,et al. Direct importance estimation for covariate shift adaptation , 2008 .
[47] Klaus-Robert Müller,et al. True Zero-Training Brain-Computer Interfacing – An Online Study , 2014, PloS one.
[48] Yufeng Ke,et al. Cross-Dataset Variability Problem in EEG Decoding With Deep Learning , 2020, Frontiers in Human Neuroscience.
[49] Maher Moakher,et al. A Differential Geometric Approach to the Geometric Mean of Symmetric Positive-Definite Matrices , 2005, SIAM J. Matrix Anal. Appl..