Prof. Dr. Klaus-Robert Müller - Publications

Note that the PDFs available on this web page are the authors' draft versions of the respective papers. The authoratative versions must be retrieved from the publisher.

2017

Journal papers

G. Montavon, S. Lapuschkin, A. Binder, W. Samek, K. R. Müller, Explaining nonlinear classification decisions with deep Taylor decomposition
Pattern Recognition, 65:211 - 222, 2017 [bibtex] [url]

2016

Journal papers

B. Blankertz, L. Acqualagna, S. Dähne, S. Haufe, M. Schultze-Kraft, I. Sturm, M. Uscumlic, M. Wenzel, G. Curio, K. Müller, The Berlin Brain-Computer Interface: Progress Beyond Communication and Control, Open Access
Frontiers in neuroscience, 10:530, 2016 [bibtex] [url]

S. Brandl, L. Frolich, J. Höhne, K. R. Müller, W. Samek, Brain-Computer Interfacing under Distraction: An Evaluation Study
Journal of Neural Engineering, 13(5):056012, 2016 [bibtex]

J. Höhne, D. Bartz, M. N. Hebart, K. R. Müller, B. Blankertz, Analyzing neuroimaging data with subclasses: a shrinkage approach
NeuroImage, 124, Part A:740-751, 2016 [bibtex] [pdf] [url]

W. Samek, D. A. Blythe, G. Curio, K. R. Müller, B. Blankertz, V. V. Nikulin, Multiscale temporal neural dynamics predict performance in a complex sensorimotor task
NeuroImage, Elsevier, 141:291-303, 2016 [bibtex]

W. Samek, A. Binder, G. Montavon, S. Lapuschkin, K. R. Müller, Evaluating the visualization of what a Deep Neural Network has learned
IEEE Transactions on Neural Networks and Learning Systems, 2016 [bibtex] [url]

C. Sannelli, C. Vidaurre, K. R. Müller, B. Blankertz, Ensembles of adaptive spatial filters increase BCI performance: an online evaluation
Journal of neural engineering, 13(4):046003, 2016 [bibtex] [pdf] [url]

M. S. Treder, A. K. Porbadnigk, F. Shahbazi, K. R. Müller, B. Blankertz, The LDA beamformer: optimal estimation of ERP source time series using linear discriminant analysis
NeuroImage, 129:279-291, 2016 [bibtex] [url]

A. Von Lühmann, H. Wabnitz, T. Sander, K. R. Müller, M3BA: A Mobile, Modular, Multimodal Biosignal Acquisition architecture for miniaturized EEG-NIRS based hybrid BCI and monitoring
IEEE Transactions on Biomedical Engineering, PP(99):1-1, 2016 [bibtex]

M. A. Wenzel, R. Schultze-Kraft, F. C. Meinecke, F. Cardinaux, T. Kemp, K. R. Müller, G. Curio, B. Blankertz, EEG-based usability assessment of 3D shutter glasses
Journal of neural engineering, 13(1):016003, 2016 [bibtex] [url]

Conference papers

F. Arbabzadah, G. Montavon, K. R. Müller, W. Samek, Identifying Individual Facial Expressions by Deconstructing a Neural Network
Pattern Recognition: 38th German Conference, GCPR 2016, Hannover, Germany, September 12-15, 2016, Proceedings, Springer International Publishing, 2016 [bibtex] [url]

A. Binder, S. Bach, G. Montavon, K. R. Müller, W. Samek, Layer-Wise Relevance Propagation for Deep Neural Network Architectures
Information Science and Applications (ICISA) 2016, Springer Singapore, 2016 [bibtex] [url]

A. Binder, G. Montavon, S. Lapuschkin, K. R. Müller, W. Samek, Layer-Wise Relevance Propagation for Neural Networks with Local Renormalization Layers
Artificial Neural Networks and Machine Learning - ICANN 2016: 25th International Conference on Artificial Neural Networks, Barcelona, Spain, September 6-9, 2016, Proceedings, Part II, Springer International Publishing, 2016 [bibtex] [url]

S. Brandl, K. R. Müller, W. Samek, Classification of motor imagery with distractions
6th International BCI Meeting in Asilomar, 2016 [bibtex]

S. Lapuschkin, A. Binder, G. Montavon, K. R. Müller, W. Samek, Analyzing Classifiers: Fisher Vectors and Deep Neural Networks
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016 [bibtex]

G. Montavon, K. R. Müller, M. Cuturi, Wasserstein Training of Restricted Boltzmann Machines
Advances In Neural Information Processing Systems 29, Curran Associates, Inc., 2016 [bibtex]

A. Von Lühmann, K. R. Müller, M3BA: New Technology for Mobile Hybrid BCIs
Proceedings of the 6th International Brain-Computer Interface Meeting 2016, 2016 [bibtex]

A. Von Lühmann, H. Wabnitz, T. Sander, K. R. Müller, Miniaturized CW NIRS for integration and hybridization with mobile EEG / ECG / EMG and Accelerometer
Proceedings of the Society for functional Near Infrared Spectroscopy Biennial Meeting 2016, 2016 [bibtex]

2015

Journal papers

L. Acqualagna, S. Bosse, A. K. Porbadnigk, G. Curio, K. R. Müller, T. Wiegand, B. Blankertz, EEG-based classification of video quality perception using steady state visual evoked potentials (SSVEPs)
Journal of neural engineering, 12(2):026012, 2015 [bibtex] [url]

S. Bach, A. Binder, G. Montavon, F. Klauschen, K. R. Müller, W. Samek, On Pixel-wise Explanations for Non-Linear Classifier Decisions by Layer-wise Relevance Propagation
PLOS ONE, 10(7):e0130140, 2015 [bibtex] [url]

S. Dähne, F. Biessman, W. Samek, S. Haufe, D. Goltz, C. Gundlach, A. Villringer, S. Fazli, K. R. Müller, Multivariate Machine Learning Methods for Fusing Functional Multimodal Neuroimaging Data
Proceedings of the IEEE, 103(9):1507-1530, 2015 [bibtex] [url]

S. Fazli, S. Dähne, W. Samek, F. Biessmann, K. R. Müller, Learning from more than one data source: data fusion techniques for sensorimotor rhythm-based Brain-Computer Interfaces
Proceedings of the IEEE, 103(6):891-906, 2015 [bibtex]

J. Hahne, S. Dähne, H. Hwang, , K. R. Müller, L. C. Parra, Concurrent Adaptation of Human and Machine Improves Simultaneous and Proportional Myoelectric Control
IEEE Transactions on Neural Systems and Rehabilitation Engineering, IEEE, 23(4):1534-4320, 2015 [bibtex]

G. Müller-Putz, R. Leeb, M. Tangermann, J. Höhne, A. Kübler, F. Cincotti, D. Mattia, R. Rupp, K. R. Müller, J. Millan, Towards Noninvasive Hybrid Brain Computer Interfaces: Framework, Practice, Clinical Application, and Beyond
Proceedings of the IEEE, PP(99):1-18, 2015 [bibtex] [url]

I. Winkler, S. Haufe, A. Porbadnigk, K. R. Müller, S. Dähne, Identifying Granger causal relationships between neural power dynamics and variables of interest
NeuroImage, 111:489-504, 2015 [bibtex] [url]

D. Wong, H. Hwang, S. Dähne, K. R. Müller, S. Lee, Effect of Higher Frequency on the Classification of Steady State Visual Evoked Potentials, accepted
Journal of Neural Engineering, 2015 [bibtex]

Conference papers

S. Brandl, J. Höhne, K. R. Müller, W. Samek, Bringing BCI into everyday life: Motor imagery in a pseudo realistic environment
Proceedings of the 2015 International IEEE Conference on Neural Engineering (NER), 2015 [bibtex]

L. Frolich, I. Winkler, K. R. Müller, W. Samek, Investigating effects of different artefact types on Motor Imagery BCI
Conf Proc IEEE Eng Med Biol Soc (EMBC), 2015 [bibtex]

S. T. Hansen, I. Winkler, L. K. Hansen, K. R. Müller, S. Dähne, Fusing Simultaneous EEG and fMRI Using Functional and Anatomical Information
International Workshop on Pattern Recognition in Neuroimaging, 2015, 2015 [bibtex]

W. Samek, K. R. Müller, Tacking noise, artifacts and nonstationarity in BCI with robust divergences
Proceedings of the European Signal Processing Conference (EUSIPCO), 2015 [bibtex]

2014

Journal papers

D. A. Blythe, S. Haufe, K. R. Müller, V. V. Nikulin, The effect of linear mixing in the EEG on Hurst exponent estimation, In press
NeuroImage, 2014 [bibtex] [url]

S. Dähne, F. C. Meinecke, S. Haufe, J. Höhne, M. Tangermann, K. R. Müller, V. V. Nikulin, SPoC: a novel framework for relating the amplitude of neuronal oscillations to behaviorally relevant parameters
NeuroImage, 86(0):111-122, 2014 [bibtex] [url]

S. Dähne, V. V. Nikulin, D. Ramírez, P. J. Schreier, K. R. Müller, S. Haufe, Finding brain oscillations with power dependencies in neuroimaging data
NeuroImage, 96:334-348, 2014 [bibtex] [pdf] [url]

M. Gaebler, F. Biessmann, J. Lamke, K. R. Müller, H. Walter, S. Hetzer, Stereoscopic depth increases intersubject correlations of brain networks
NeuroImage, Elsevier, 100:427-434, 2014 [bibtex]

J. Höhne, E. M. Holz, P. Staiger-Sälzer, K. R. Müller, A. Kübler, M. Tangermann, Motor Imagery for Severely Motor-Impaired Patients: Evidence for Brain-Computer Interfacing as Superior Control Solution, Open Access
PloS one, Public Library of Science, 9(8):e104854, 2014 [bibtex] [url]

C. Habermehl, J. Steinbrink, K. R. Müller, S. Haufe, Optimizing the regularization for image reconstruction of cerebral diffuse optical tomography
Journal of Biomedical Optics, 19(9):096006, 2014 [bibtex]

M. Kawanabe, W. Samek, K. R. Müller, C. Vidaurre, Robust Common Spatial filters with a Maxmin Approach
Neural Computation, 26(2):1-28, 2014 [bibtex] [url]

P. Kindermans, M. Tangermann, K. R. Müller, B. Schrauwen, Integrating dynamic stopping, transfer learning and language models in an adaptive zero-training ERP speller
Journal of neural engineering, 11(3):035005, 2014 [bibtex] [url]

W. Samek, M. Kawanabe, K. R. Müller, Divergence-based Framework for Common Spatial Patterns Algorithms
Biomedical Engineering, IEEE Reviews in, 7:50-72, 2014 [bibtex] [url]

H. Suk, S. Fazli, J. Mehnert, K. R. Müller, S. Lee, Predicting BCI subject performance using probabilistic spatio-temporal filters, Open Access
PloS one, Public Library of Science, 9(2):e87056, 2014 [bibtex]

Book chapters

A. Binder, W. Samek, K. R. Müller, M. Kawanabe, Machine Learning for Visual Concept Recognition and Ranking for Images
Towards the Internet of Services: The THESEUS Program, Cognitive Technologies, 2014 [bibtex] [url]

Conference papers

S. Dähne, F. Biessmann, F. C. Meinecke, J. Mehnert, S. Fazli, K. R. Müller, Multimodal integration of electrophysiological and hemodynamic signals
Brain-Computer Interface (BCI), 2014 International Winter Workshop on, 2014 [bibtex]

S. Dähne, S. Haufe, F. Biessmann, F. Meinecke, D. Ramirez, P. Schreier, V. Nikulin, K. R. Müller, Finding brain oscillations with power dependencies in neuroimaging data
Annual Meeting of the Organization for Human Brain Mapping (OHBM), 2014, 2014 [bibtex]

S. Dähne, V. V. Nikulin, D. Ramirez, P. J. Schreier, K. R. Müller, S. Haufe, Optimizing spatial filters for the extraction of envelope-coupled neural oscillations
International Workshop on Pattern Recognition in Neuroimaging, 2014, 2014 [bibtex]

S. Dähne, J. Hahne, P. Pawletta, K. R. Müller, Boosting simultaneous and proportional myoelectric control by combining source power correlation (SPoC) and linear regression
Bernstein Conference, 2014, 2014 [bibtex]

N. Görnitz, A. K. Porbadnigk, A. Binder, C. Sannelli, M. Braun, K. R. Müller, M. Kloft, Learning and Evaluation in Presence of Non-iid Label Noise
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014 [bibtex]

J. Höhne, B. Blankertz, K. R. Müller, D. Bartz, Mean shrinkage improves the classification of ERP signals by exploiting additional label information
Proceedings of the 2014 International Workshop on Pattern Recognition in Neuroimaging, 2014 [bibtex] [pdf]

W. Samek, K. R. Müller, Information Geometry meets BCI - Spatial filtering using divergences
Brain-Computer Interface (BCI), 2014 International Winter Workshop on, 2014 [bibtex]

2013

Journal papers

A. Binder, W. Samek, K. R. Müller, M. Kawanabe, Enhanced Representation and Multi-Task Learning for Image Annotation
Computer Vision and Image Understanding, 117(5):466 - 478, 2013 [bibtex] [url]

S. Dähne, F. Biessman, F. C. Meinecke, J. Mehnert, S. Fazli, K. R. Müller, Integration of Multivariate Data Streams With Bandpower Signals
IEEE Transactions on Multimedia, 15(5):1001-1013, 2013 [bibtex] [url]

K. Hansen, G. Montavon, F. Biegler, S. Fazli, M. Rupp, M. Scheffler, O. A. v. Lilienfeld, A. Tkatchenko, K. R. Müller, Assessment and Validation of Machine Learning Methods for Predicting Molecular Atomization Energies
Journal of Chemical Theory and Computation, 9(8):3404-3419, 2013 [bibtex]

G. Montavon, M. L. Braun, T. Krueger, K. R. Müller, Analyzing Local Structure in Kernel-based Learning: Explanation, Complexity and Reliability Assessment
Signal Processing Magazine, IEEE, 30(4):62-74, 2013 [bibtex] [url]

G. Montavon, M. Rupp, V. Gobre, A. Vazquez-Mayagoitia, K. Hansen, A. Tkatchenko, K. R. Müller, O. A. v. Lilienfeld, Machine Learning of Molecular Electronic Properties in Chemical Compound Space, to appear
New Journal of Physics, Focus Issue, Novel Materials Discovery, 2013 [bibtex]

A. K. Porbadnigk, M. S. Treder, B. Blankertz, J. Antons, R. Schleicher, S. Möller, G. Curio, K. R. Müller, Single-trial analysis of the neural correlates of speech quality perception
Journal of neural engineering, 10(5):056003, 2013 [bibtex]

W. Samek, F. C. Meinecke, K. R. Müller, Transferring Subspaces Between Subjects in Brain-Computer Interfacing
IEEE transactions on bio-medical engineering, 60(8):2289-2298, 2013 [bibtex]

K. T. Schütt, H. Glawe, F. Brockherde, A. Sanna, K. R. Müller, E. Gross, How to represent crystal structures for machine learning: towards fast prediction of electronic properties
arXiv, 2013 [bibtex] [pdf] [url]

C. Vidaurre, J. Pascual, A. Ramos-Murguialday, R. Lorenz, B. Blankertz, N. Birbaumer, K. R. Müller, Neuromuscular electrical stimulation induced brain patterns to decode motor imagery
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology, 124(1):1824-1834, 2013 [bibtex] [url]

Conference papers

D. Bartz, K. R. Müller, Generalizing Analytic Shrinkage for Arbitrary Covariance Structures
Advances in Neural Information Processing Systems 26, 2013 [bibtex]

G. Montavon, K. R. Müller, Neural Networks for Computational Chemistry: Pitfalls and Recommendations
MRS Online Proceedings Library, 1523, 2013 [bibtex] [url]

W. Samek, A. Binder, K. R. Müller, Multiple Kernel Learning for Brain-Computer Interfacing
Conf Proc IEEE Eng Med Biol Soc (EMBC), 2013 [bibtex] [url]

W. Samek, D. Blythe, K. R. Müller, M. Kawanabe, Robust Spatial Filtering with Beta Divergence
Advances in Neural Information Processing Systems 26, MIT Press, 2013 [bibtex] [pdf] [url]

M. Tangermann, P. Kindermans, M. Schreuder, B. Schrauwen, K. R. Müller, Zero Training for BCI - Reality for BCI Systems Based on Event-Related Potentials
Proceedings BMT (Biomedizinische Technik) 2013 - Dreiländertagung der Deutschen, Schweizerischen und Österreichischen Gesellschaft für Biomedizinische Technik, Walter de Gruyter, Biomedical Engineering/Biomedizinische Technik, 58(SI-1), 2013 [bibtex] [url]

2012

Books

G. Montavon, G. B. Orr, K. R. Müller, (Eds.), Neural Networks: Tricks of the Trade, Reloaded
Springer, Lecture Notes in Computer Science (LNCS), 7700, 2012 [bibtex] [url]

Journal papers

F. Biessmann, Y. Murayama, N. K. Logothetis, K. R. Müller, F. C. Meinecke, Improved decoding of neural activity from fMRI signals using non-separable spatiotemporal deconvolutions
NeuroImage, 61(4):1031-1042, 2012 [bibtex] [pdf]

A. Binder, K. R. Müller, M. Kawanabe, On Taxonomies for Multi-class Image Categorization
International Journal of Computer Vision, 99(3):281-301, 2012 [bibtex] [url]

A. Binder, S. Nakajima, M. Kloft, C. Müller, W. Samek, U. Brefeld, K. R. Müller, M. Kawanabe, Insights from Classifying Visual Concepts with Multiple Kernel Learning
PLoS ONE, 7(8), 2012 [bibtex] [url]

D. A. Blythe, P. v. Bünau, F. C. Meinecke, K. R. Müller, Feature Extraction for Change-Point Detection using Stationary Subspace Analysis
IEEE Transactions on Neural Networks and Learning Systems, 23(4):631-643, 2012 [bibtex] [pdf]

S. Fazli, J. Mehnert, J. Steinbrink, G. Curio, A. Villringer, K. R. Müller, B. Blankertz, Enhanced performance by a Hybrid NIRS-EEG Brain Computer Interface, Open Access
NeuroImage, 59(1):519-529, 2012 [bibtex] [url]

S. Haufe, V. V. Nikulin, K. R. Müller, G. Nolte, A critical assessment of connectivity measures for EEG data: a simulation study
NeuroImage, 64:120-133, 2012 [bibtex] [pdf] [url]

F. J. Kiraly, P. v. Bünau, F. C. Meinecke, D. A. Blythe, K. R. Müller, Algebraic Geometric Comparison of Probability Distributions
Journal of Machine Learning Research, 13:855-903, 2012 [bibtex] [pdf]

W. Samek, C. Vidaurre, K. R. Müller, M. Kawanabe, Stationary Common Spatial Patterns for Brain-Computer Interfacing
Journal of Neural Engineering, 9(2):026013, 2012 [bibtex] [url]

S. Scholler, S. Bosse, M. S. Treder, B. Blankertz, G. Curio, K. R. Müller, T. Wiegand, Towards a Direct Measure of Video Quality Perception using EEG
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, 21(5):2619-2629, 2012 [bibtex] [pdf] [url]

M. Tangermann, K. R. Müller, A. Aertsen, N. Birbaumer, C. Braun, C. Brunner, R. Leeb, C. Mehring, K. Miller, G. Müller-Putz, G. Nolte, G. Pfurtscheller, H. Preissl, G. Schalk, A. Schlögl, C. Vidaurre, S. Waldert, B. Blankertz, Review of the BCI Competition IV, Open Access
Frontiers in neuroscience, 6(55), 2012 [bibtex] [url]

Book chapters

B. Blankertz, M. Tangermann, K. R. Müller, BCI applications for the general population
Brain-Computer Interfaces - Principles and Practice, Oxford University Press, 2012 [bibtex]

F. J. Király, A. Ziehe, K. R. Müller, An Algebraic Method for Approximate Rank One Factorization of Rank Deficient Matrices
Latent Variable Analysis and Signal Separation, Springer Berlin / Heidelberg, Lecture Notes in Computer Science, 2012 [bibtex] [url]

G. Montavon, K. R. Müller, Deep Boltzmann Machines and the Centering Trick
Neural Networks: Tricks of the trade, Reloaded, Springer, LNCS, 7700, 2012 [bibtex] [pdf] [url]

Conference papers

F. Biessmann, J. Papaioannou, A. Harth, M. L. Jugel, K. R. Müller, M. Braun, Quantifying Spatiotemporal Dynamics of Twitter Replies to News Feeds
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2012 [bibtex] [pdf]

S. Dähne, F. Meinecke, S. Haufe, J. Höhne, M. Tangermann, V. Nikulin, K. R. Müller, Multi-variate correlation of power spectral density
Annual Meeting of the Organization for Human Brain Mapping (OHBM), 2012, 2012 [bibtex]

F. J. Kiraly, P. v. Bünau, J. S. Müller, D. A. Blythe, F. C. Meinecke, K. R. Müller, Regression for sets of polynomial equations
JMLR Workshop and Conference Proc. Vol. 22, 2012 [bibtex] [pdf]

G. Montavon, M. Braun, K. R. Müller, Deep Boltzmann Machines as Feed-Forward Hierarchies
International Conference on Artificial Intelligence and Statistics (AISTATS), 2012 [bibtex] [pdf]

G. Montavon, K. Hansen, S. Fazli, M. Rupp, F. Biegler, A. Ziehe, A. Tkatchenko, O. A. v. Lilienfeld, K. R. Müller, Learning Invariant Representations of Molecules for Atomization Energy Prediction
Advances in Neural Information Processing Systems 25, 2012 [bibtex] [url]

J. Pascual, F. Velasco-Álvarez, K. R. Müller, C. Vidaurre, First Study Towards Linear Control of an Upper-Limb Neuroprosthesis with an EEG-based Brain-Computer Interface
Conf Proc IEEE Eng Med Biol Soc, 2012, 2012 [bibtex] [url]

W. Samek, K. R. Müller, M. Kawanabe, C. Vidaurre, Brain-Computer Interfacing in Discriminative and Stationary Subspaces
Conf Proc IEEE Eng Med Biol Soc (EMBC), 2012 [bibtex] [url]

C. Sannelli, C. Vidaurre, K. R. Müller, B. Blankertz, Common Spatial Pattern Patches: online evaluation on naive users
Conf Proc IEEE Eng Med Biol Soc, 2012, 2012 [bibtex] [pdf]

2011

Journal papers

D. Bartz, K. Hatrick, C. Hesse, K. R. Müller, S. Lemm, Directional Variance Adjustment: a novel covariance estimator for high dimensional portfolio optimization
arXiv, 2011 [bibtex]

F. Biessmann, S. M. Plis, F. C. Meinecke, T. Eichele, K. R. Müller, Analysis of Multimodal Neuroimaging Data
Biomedical Engineering, IEEE Reviews in, 4:26-58, 2011 [bibtex]

A. Binder, S. Nakajima, M. Kloft, C. Müller, W. Samek, U. Brefeld, K. R. Müller, M. Kawanabe, Insights from Classifying Visual Concepts with Multiple Kernel Learning
arXiv, 2011 [bibtex] [url]

B. Blankertz, S. Lemm, M. S. Treder, S. Haufe, K. R. Müller, Single-trial analysis and classification of ERP components - a tutorial
NeuroImage, 56:814-825, 2011 [bibtex] [pdf] [url]

S. Dähne, K. R. Müller, , M. Tangermann, Slow Feature Analysis as a Potential Preprocessing Tool in BCI
International Journal of Bioelectromagnetism, 13(2):100-101, 2011 [bibtex] [url]

S. Fazli, M. Danóczy, J. Schelldorfer, K. R. Müller, L1-penalized Linear Mixed-Effects Models for high dimensional data with application to BCI
NeuroImage, 56(4):2100 - 2108, 2011 [bibtex] [pdf] [url]

J. Höhne, M. Schreuder, B. Blankertz, K. R. Müller, M. Tangermann, Novel Paradigms for Auditory ERP Spellers with Spatial Hearing: Two Online Studies
International Journal of Bioelectromagnetism, 13(2):96-97, 2011 [bibtex] [url]

K. Hansen, D. Baehrens, T. Schroeter, M. Rupp, K. R. Müller, Visual Interpretation of Kernel-Based Prediction Models
Molecular Informatics, 30(9):817-826, 2011 [bibtex] [url]

S. Haufe, R. Tomioka, T. Dickhaus, C. Sannelli, B. Blankertz, G. Nolte, K. R. Müller, Large-Scale EEG/MEG Source Localization with Spatial Flexibility
NeuroImage, 54:851-859, 2011 [bibtex] [pdf] [url]

S. Lemm, B. Blankertz, T. Dickhaus, K. R. Müller, Introduction to machine learning for brain imaging
NeuroImage, 56:387-399, 2011 [bibtex] [pdf] [url]

K. R. Müller, B. Blankertz, M. Tangermann, G. Curio, Forschen an einer neuen Schnittstelle zum Gehirn: Das Berliner Brain-Computer-Interface
Nova Acta Leopoldina, 110(377):235-257, 2011 [bibtex] [url]

J. Müller, P. v. Bünau, F. Meinecke, F. Király, K. R. Müller, The Stationary Subspace Analysis Toolbox
Journal of Machine Learning Research, 12:3065-3069, 2011 [bibtex] [pdf]

G. Montavon, M. Braun, K. R. Müller, Kernel analysis of deep networks
Journal of Machine Learning Research, 12:2563-2581, 2011 [bibtex] [pdf]

F. Rathke, K. Hansen, U. Brefeld, K. R. Müller, StructRank: A New Approach for Ligand-Based Virtual Screening
J. Chem. Inf. Model., 51:83-92, 2011 [bibtex]

C. Sannelli, C. Vidaurre, K. R. Müller, B. Blankertz, Common Spatial Pattern Patches - an Optimized Filter Ensemble for Adaptive Brain-Computer Interfaces
Journal of neural engineering, 8(2):025012 (7pp), 2011 [bibtex] [url]

C. Vidaurre, M. Kawanabe, P. v. Bünau, B. Blankertz, K. R. Müller, Toward Unsupervised Adaptation of LDA for Brain-Computer Interfaces
IEEE transactions on bio-medical engineering, 58(3):587 -597, 2011 [bibtex] [url]

C. Vidaurre, C. Sannelli, K. R. Müller, B. Blankertz, Machine-Learning Based Co-adaptive Calibration
Neural computation, 23(3):791-816, 2011 [bibtex] [pdf] [url]

C. Vidaurre, C. Sannelli, K. R. Müller, B. Blankertz, Co-adaptive calibration to improve BCI efficiency
Journal of neural engineering, 8(2):025009 (8pp), 2011 [bibtex] [url]

Conference papers

A. Binder, W. Samek, M. Kloft, C. Müller, K. R. Müller, M. Kawanabe, The Joint Submission of the TU Berlin and Fraunhofer FIRST (TUBFI) to the ImageCLEF2011 Photo Annotation Task
CLEF (Notebook Papers/Labs/Workshop), 2011 [bibtex] [pdf]

D. Blythe, W. Samek, K. R. Müller, Stationary Linear Discriminant Analysis - Classifying Non-Stationary Features in Brain-Computer Interfacing, Conference Abstract: Bernstein Conference on Computational Neuroscience (BCCN '11)
Frontiers in Neuroscience, 2011 [bibtex] [url]

S. Fazli, M. Danóczy, J. Schelldorfer, K. R. Müller, $ll_1$-Penalized Linear Mixed-Effects Models for BCI
Artificial Neural Networks and Machine Learning-ICANN 2011, Springer-Verlag, 2011 [bibtex]

R. Jenssen, M. Kloft, A. Zien, S. Sonnenburg, K. R. Müller, A New Scatter-Based Multi-Class Support Vector Machine
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing (MLSP), 2011 [bibtex]

G. Montavon, M. Braun, K. R. Müller, Importance of Cross-Layer Cooperation for Learning Deep Feature Hierarchies
NIPS Workshop on Deep Learning and Unsupervised Feature Learning, 2011 [bibtex] [pdf]

A. K. Porbadnigk, S. Scholler, B. Blankertz, A. Ritz, M. Born, R. Scholl, K. R. Müller, G. Curio, M. S. Treder, Revealing the Neural Response to Imperceptible Peripheral Flicker with Machine Learning
Conf Proc IEEE Eng Med Biol Soc, 2011:3692-3695, 2011 [bibtex] [pdf]

2010

Journal papers

D. Baehrens, T. Schroeter, S. Harmeling, M. Kawanabe, K. Hansen, K. R. Müller, How to Explain Individual Classification Decisions
JMLR, 11:1803-1831, 2010 [bibtex] [url]

B. Blankertz, C. Sannelli, S. Halder, E. M. Hammer, A. Kübler, K. R. Müller, G. Curio, T. Dickhaus, Neurophysiological Predictor of SMR-Based BCI Performance
NeuroImage, 51(4):1303-1309, 2010 [bibtex] [pdf] [url]

B. Blankertz, M. Tangermann, C. Vidaurre, S. Fazli, C. Sannelli, S. Haufe, C. Maeder, L. E. Ramsey, I. Sturm, G. Curio, K. R. Müller, The Berlin Brain-Computer Interface: Non-Medical Uses of BCI Technology, Open Access
Frontiers in neuroscience, 4:198, 2010 [bibtex] [url]

S. Haufe, G. Nolte, K. R. Müller, N. Krämer, Sparse Causal Discovery in Multivariate Time Series
JMLR W&CP, 6:97-106, 2010 [bibtex] [pdf]

S. Haufe, R. Tomioka, G. Nolte, K. R. Müller, M. Kawanabe, Modeling sparse connectivity between underlying brain sources for EEG/MEG
IEEE transactions on bio-medical engineering, 57(8):1954 - 1963, 2010 [bibtex] [pdf] [url]

Y. Murayama, F. Biessmann, F. C. Meinecke, K. R. Müller, M. Augath, A. Öltermann, N. K. Logothetis, Relationship between neural and hemodynamic signals during spontaneous activity studied with temporal kernel CCA
Magnetic Resonance Imaging, 28(8):1095-1103, 2010 [bibtex] [url]

G. Nolte, K. R. Müller, Localizing and estimating causal relations of interacting brain rhythms, Open Access
Frontiers in human neuroscience, 4:209, 2010 [bibtex] [url]

J. d. R. Millán, R. Rupp, G. Müller-Putz, R. Murray-Smith, C. Giugliemma, M. Tangermann, C. Vidaurre, F. Cincotti, A. Kübler, R. Leeb, C. Neuper, K. R. Müller, D. Mattia, Combining Brain-Computer Interfaces and Assistive Technologies: State-of-the-Art and Challenges, Open Access
Frontiers in Neuroprosthetics, 4, 2010 [bibtex] [url]

K. Rieck, T. Krueger, U. Brefeld, K. R. Müller, Approximate Tree Kernels
Journal of Machine Learning Research, 11(Feb):555-580, 2010 [bibtex] [pdf]

M. Rupp, T. Schroeter, R. Steri, H. Zettl, E. Proschak, K. Hansen, O. Rau, O. Schwarz, L. Müller-Kuhrt, M. Schubert-Zsilavecz, K. R. Müller, G. Schneider, From machine learning to natural product derivatives selectively activating transcription factor PPAR$amma$
ChemMedChem, 5(2):191-194, 2010 [bibtex] [url]

C. Sannelli, T. Dickhaus, S. Halder, E. M. Hammer, K. R. Müller, B. Blankertz, On optimal channel configurations for SMR-based brain-computer interfaces
Brain topography, 23(2):186-193, 2010 [bibtex] [pdf] [url]

R. Steri, M. Rupp, E. Proschak, T. Schroeter, H. Zettl, K. Hansen, O. Schwarz, L. Müller-Kuhrt, K. R. Müller, G. Schneider, M. Schubert-Zsilavecz, Truxillic acid derivatives act as peroxisome proliferator-activated receptor [gamma] activators
Bioorganic & Medicinal Chemistry Letters, 20(9):2920-2923, 2010 [bibtex] [url]

R. Tomioka, K. R. Müller, A regularized discriminative framework for EEG analysis with application to brain-computer interface
NeuroImage, 49:415-432, 2010 [bibtex] [url]

B. Venthur, S. Scholler, J. Williamson, S. Dähne, M. S. Treder, M. T. Kramarek, K. R. Müller, B. Blankertz, Pyff - A Pythonic Framework for Feedback Applications and Stimulus Presentation in Neuroscience, Open Access
Frontiers in neuroscience, 4:179, 2010 [bibtex] [url]

Book chapters

B. Blankertz, M. Tangermann, C. Vidaurre, T. Dickhaus, C. Sannelli, F. Popescu, S. Fazli, M. Danóczy, G. Curio, K. R. Müller, Detecting Mental States by Machine Learning Techniques: The Berlin Brain-Computer Interface
Brain-Computer Interfaces (Revolutionizing Human-Computer Interaction), Springer, The Frontiers Collection, 2010 [bibtex] [url]

G. Nolte, A. Ziehe, N. Krämer, F. Popescu, K. R. Müller, Comparison of Granger Causality and Phase Slope Index
Causality: Objectives and Assessment, JMLR Workshop and Conference Proceedings, 6:267-276, 2010 [bibtex] [url]

A. Schlögl, C. Vidaurre, K. R. Müller, Adaptive Methods in BCI Research - An Introductory Tutorial
Brain-Computer Interfaces, Springer, The Frontiers Collection, 2010 [bibtex] [url]

Conference papers

P. v. Bünau, F. C. Meinecke, S. Scholler, K. R. Müller, Finding Stationary Brain Sources in EEG Data
Proceedings of the 32nd Annual Conference of the IEEE EMBS, 2010 [bibtex]

J. Höhne, M. Schreuder, B. Blankertz, K. R. Mueller, M. Tangermann, Novel paradigms for auditory P300 Spellers with spatial hearing: two online studies, Conference Abstract: Bernstein Conference on Computational Neuroscience 2010
Frontiers in computational neuroscience, 2010 [bibtex] [url]

S. Haufe, R. Tomioka, T. Dickhaus, C. Sannelli, B. Blankertz, G. Nolte, K. R. Müller, Localization of class-related mu-rhythm desynchronization in motor imagery based Brain-Computer Interface sessions
Conf Proc IEEE Eng Med Biol Soc, 2010:5137-5140, 2010 [bibtex] [pdf] [url]

S. Haufe, R. Tomioka, G. Nolte, K. R. Müller, M. Kawanabe, Modeling the Connectivity of Neural Ensembles Underlying EEG/MEG, Conference Abstract: Bernstein Conference on Computational Neuroscience 2010
Frontiers in computational neuroscience, 2010 [bibtex] [url]

G. Montavon, M. Braun, K. R. Müller, Layer-wise analysis of deep networks with Gaussian kernels
Advances in Neural Information Processing Systems 23, 2010 [bibtex] [pdf]

C. Sannelli, C. Vidaurre, K. R. Müller, B. Blankertz, Common Spatial Pattern Patches - an Optimized Filter Ensemble for Adaptive Brain-Computer Interfaces
Conf Proc IEEE Eng Med Biol Soc, 2010:4351-4354, 2010 [bibtex] [pdf] [url]

C. Sannelli, C. Vidaurre, K. R. Müller, B. Blankertz, Common Spatial Pattern Patches - an Optimized Spatial Filter for Adaptive BCIs, Conference Abstract: Bernstein Conference on Computational Neuroscience 2010
Frontiers in computational neuroscience, 2010 [bibtex] [url]

2009

Journal papers

P. v. Bünau, F. C. Meinecke, F. Király, K. R. Müller, Finding Stationary Subspaces in Multivariate Time Series
Physical Review Letters, 103:214101, 2009 [bibtex]

F. Biessmann, F. C. Meinecke, A. Gretton, A. Rauch, G. Rainer, N. Logothetis, K. R. Müller, Temporal Kernel Canonical Correlation Analysis and its Application in Multimodal Neuronal Data Analysis
Machine Learning, 79(1-2):5-27, 2009 [bibtex] [pdf] [url]

S. Fazli, F. Popescu, M. Danóczy, B. Blankertz, K. R. Müller, C. Grozea, Subject-independent mental state classification in single trials
Neural networks : the official journal of the International Neural Network Society, 22(9):1305-1312, 2009 [bibtex] [url]

K. Hansen, S. Mika, T. Schroeter, A. Sutter, A. t. Laak, T. Steger-Hartmann, N. Heinrich, K. R. Müller, Benchmark Data Set for in Silico Prediction of Ames Mutagenicity
J. Chem. Inf. Model., 49(9):2077-2081, 2009 [bibtex] [url]

S. Lemm, K. R. Müller, G. Curio, A Generalized Framework for Quantifying the Dynamics of EEG Event-Related Desynchronization, Open Access
PLoS Comput Biol, Public Library of Science, 5(8), 2009 [bibtex] [url]

C. Sannelli, M. Braun, K. R. Müller, Improving BCI performance by task-related trial pruning
Neural Networks, 22:1295-1304, 2009 [bibtex] [url]

S. Wahl, K. Rieck, P. Laskov, P. Domschitz, K. R. Müller, Securing IMS against Novel Threats
Bell Labs Technical Journal, 14(1):243-257, 2009 [bibtex] [pdf]

J. Williamson, R. Murray-Smith, B. Blankertz, M. Krauledat, K. R. Müller, Designing for uncertain, asymmetric control: Interaction design for brain-computer interfaces
Int J Hum Comput Stud, 67(10):827-841, 2009 [bibtex] [url]

Conference papers

P. v. Bünau, F. C. Meinecke, K. R. Müller, Stationary Subspace Analysis
ICA, 2009 [bibtex] [url]

B. Blankertz, K. R. Müller, G. Curio, Neuronal Correlates of Emotions in Human-Machine Interaction, Eighteenth Annual Computational Neuroscience Meeting: CNS*2009
BMC Neuroscience 2009, 10:(Suppl 1):P80, 2009 [bibtex] [url]

B. Blankertz, C. Sannelli, S. Halder, E. Hammer, A. Kübler, K. R. Müller, G. Curio, T. Dickhaus, Predicting BCI Performance to Study BCI Illiteracy
7th NFSI & ICBEM 2009, 2009 [bibtex] [pdf]

T. Dickhaus, C. Sannelli, K. R. Müller, G. Curio, B. Blankertz, Predicting BCI Performance to Study BCI Illiteracy, Eighteenth Annual Computational Neuroscience Meeting: CNS*2009
BMC Neuroscience 2009, 10:(Suppl 1):P84, 2009 [bibtex] [url]

M. Kawanabe, C. Vidaurre, B. Blankertz, K. R. Müller, A maxmin approach to optimize spatial filters for EEG single-trial classification
Proceedings of IWANN 09, Part I, LNCS, 2009 [bibtex] [pdf]

M. Kawanabe, C. Vidaurre, S. Schoeller, B. Blankertz, K. R. Mueller, Robust Common Spatial Filters with a Maxmin Approach
EMBS-Conference, 2009 [bibtex]

M. Kloft, U. Brefeld, S. Sonnenburg, P. Laskov, K. R. Müller, A. Zien, Efficient and Accurate Lp-Norm Multiple Kernel Learning
Advances in Neural Information Processing Systems 22, MIT Press, 2009 [bibtex] [pdf]

F. C. Meinecke, P. v. Bünau, M. Kawanabe, K. R. Müller, Learning invariances with Stationary Subspace Analysis
Computer Vision Workshops (ICCV Workshops), 2009 IEEE 12th International Conference on, 2009 [bibtex]

S. Nakajima, A. Binder, C. Müller, W. Wojcikiewicz, M. Kloft, U. Brefeld, K. R. Müller, M. Kawanabe, Multiple Kernel Learning for Object Classification
Proceedings of the 12th Workshop on Information-based Induction Sciences, 2009 [bibtex] [pdf]

M. Tangermann, M. Krauledat, K. Grzeska, M. Sagebaum, B. Blankertz, C. Vidaurre, K. R. Müller, Playing Pinball with non-invasive BCI
Advances in Neural Information Processing Systems 21, December 8-11, 2008, MIT Press, 2009 [bibtex] [pdf]

Technical reports

R. Jenssen, M. Kloft, A. Zien, S. Sonnenburg, K. R. Müller, A Multi-Class Support Vector Machine Based on Scatter Criteria
Technische Universität Berlin, 2009 [bibtex] [url]

2008

Journal papers

B. Blankertz, F. Losch, M. Krauledat, G. Dornhege, G. Curio, K. R. Müller, The Berlin Brain-Computer Interface: Accurate performance from first-session in BCI-naive subjects
IEEE transactions on bio-medical engineering, 55(10):2452-2462, 2008 [bibtex] [pdf] [url]

B. Blankertz, R. Tomioka, S. Lemm, M. Kawanabe, K. R. Müller, Optimizing Spatial Filters for Robust EEG Single-Trial Analysis
IEEE Signal Processing Magazine, 25(1):41-56, 2008 [bibtex] [pdf] [url]

M. L. Braun, J. Buhmann, K. R. Müller, On Relevant Dimensions in Kernel Feature Spaces
Journal of Machine Learning Research, 9:1875-1908, 2008 [bibtex]

S. Haufe, V. V. Nikulin, A. Ziehe, K. R. Müller, G. Nolte, Combining sparsity and rotational invariance in EEG/MEG source reconstruction
NeuroImage, 42(2):726-738, 2008 [bibtex] [pdf] [url]

M. Krauledat, M. Tangermann, B. Blankertz, K. R. Müller, Towards Zero Training for Brain-Computer Interfacing, Open Access
PloS one, Public Library of Science, 3(8):e2967, 2008 [bibtex] [pdf] [url]

K. R. Müller, M. Tangermann, G. Dornhege, M. Krauledat, G. Curio, B. Blankertz, Machine learning for real-time single-trial EEG-analysis: From brain-computer interfacing to mental state monitoring
Journal of neuroscience methods, 167(1):82-90, 2008 [bibtex] [pdf] [url]

A. Nijholt, D. Tan, G. Pfurtscheller, C. Brunner, J. Millán, B. Allison, B. Grainmann, F. Popescu, B. Blankertz, K. R. Müller, Brain-Computer Interfacing for Intelligent Systems
IEEE Intelligent Systems, 23(3):72-79, 2008 [bibtex] [pdf] [url]

G. Nolte, A. Ziehe, V. Nikulin, A. Schlögl, N. Krämer, T. Brismar, K. R. Müller, Robustly Estimating the Flow Direction of Information in Complex Physical Systems
Physical Review Letters, 100:234101, 2008 [bibtex] [pdf] [url]

A. Schwaighofer, T. Schroeter, S. Mika, K. Hansen, A. t. Laak, P. Lienau, A. Reichel, N. Heinrich, K. R. Müller, A Probabilistic Approach to Classifying Metabolic Stability
Journal of Chemical Information and Modelling, 48(4):785-796, 2008 [bibtex] [pdf] [url]

Book chapters

B. Blankertz, M. Tangermann, F. Popescu, M. Krauledat, S. Fazli, M. Danóczy, G. Curio, K. R. Müller, The Berlin Brain-Computer Interface
WCCI 2008 Plenary/Invited Lectures, Springer, LNCS, 5050:79-101, 2008 [bibtex] [pdf] [url]

P. Laskov, K. Rieck, K. R. Müller, Machine Learning for Intrusion Detection
Mining Massive Data Sets for Security, IOS press, 2008 [bibtex]

Conference papers

B. Blankertz, M. Kawanabe, R. Tomioka, F. Hohlefeld, V. Nikulin, K. R. Müller, Invariant Common Spatial Patterns: Alleviating Nonstationarities in Brain-Computer Interfacing
Advances in Neural Information Processing Systems 20, MIT Press, 2008 [bibtex] [pdf]

S. Haufe, V. V. Nikulin, A. Ziehe, K. R. Müller, G. Nolte, Estimating vector fields using sparse basis field expansions
Advances in Neural Information Processing Systems 21, MIT Press, 2008 [bibtex] [pdf]

K. Rieck, S. Wahl, P. Laskov, P. Domschitz, K. R. Müller, A Self-Learning System for Detection of Anomalous SIP Messages
Principles, Systems and Applications of IP Telecommunications (IPTCOMM), Second International Conference, LNCS, 2008 [bibtex] [pdf]

2007

Books

G. Dornhege, J. d. R. Millán, T. Hinterberger, D. McFarland, K. R. Müller, (Eds.), Toward Brain-Computer Interfacing
MIT Press, 2007 [bibtex]

Journal papers

G. Blanchard, C. Schäfer, Y. Rozenholc, K. R. Müller, Optimal dyadic decision trees
Machine Learning, 66(2-3):209-241, 2007 [bibtex] [pdf] [url]

B. Blankertz, G. Dornhege, M. Krauledat, K. R. Müller, G. Curio, The non-invasive Berlin Brain-Computer Interface: Fast Acquisition of Effective Performance in Untrained Subjects
NeuroImage, 37(2):539-550, 2007 [bibtex] [pdf] [url]

M. Kawanabe, M. Sugiyama, G. Blanchard, K. R. Müller, A new algorithm of non-Gaussian component analysis with radial kernel functions
Annals of the Institute of Statistical Mathematics, 59(1):57-75, 2007 [bibtex]

M. Krauledat, G. Dornhege, B. Blankertz, K. R. Müller, Robustifying EEG data analysis by removing outliers
Chaos and Complexity Letters, 2(3):259-274, 2007 [bibtex] [pdf]

R. Krepki, B. Blankertz, G. Curio, K. R. Müller, The Berlin Brain-Computer Interface (BBCI): towards a new communication channel for online control in gaming applications
Journal of Multimedia Tools and Applications, 33(1):73-90, 2007 [bibtex] [pdf] [url]

R. Krepki, G. Curio, B. Blankertz, K. R. Müller, Berlin Brain-Computer Interface - the HCI Communication Channel for Discovery, Special Issue on Ambient Intelligence
Int J Hum Comp Studies, 65:460-477, 2007 [bibtex] [pdf]

V. V. Nikulin, K. Linkenkaer-Hansen, G. Nolte, S. Lemm, K. R. Müller, R. J. Ilmoniemi, G. Curio, A novel mechanism for evoked responses in human brain
The European journal of neuroscience, 25:3146-54, 2007 [bibtex] [pdf]

F. Popescu, S. Fazli, Y. Badower, B. Blankertz, K. R. Müller, Single Trial Classification of Motor Imagination Using 6 Dry EEG Electrodes, Open Access
PloS one, 2(7):e637, 2007 [bibtex] [pdf] [url]

G. Rätsch, S. Sonnenburg, J. Srinivasan, H. Witte, R. Sommer, K. R. Müller, B. Schölkopf, Improving the C. elegans genome annotation using machine learning
PLoS Computational Biology, 3:e20, 2007 [bibtex] [pdf]

T. Schroeter, A. Schwaighofer, S. Mika, A. t. Laak, D. Sülzle, U. Ganzer, N. Heinrich, K. R. Müller, Predicting Lipophilicity of Drug Discovery Molecules using Gaussian Process Models
ChemMedChem, 2(9):1265-1267, 2007 [bibtex] [pdf] [url]

T. Schroeter, A. Schwaighofer, S. Mika, A. T. Laak, D. Suelzle, U. Ganzer, N. Heinrich, K. R. Müller, Estimating the Domain of Applicability for Machine Learning QSAR RModels: A Study on Aqueous Solubility of Drug Discovery Molecules
Journal of Computer Aided Molecular Design - special issue on "ADME and Physical Properties", 21(9):485-498, 2007 [bibtex] [pdf] [url]

T. Schroeter, A. Schwaighofer, S. Mika, A. T. Laak, D. Suelzle, U. Ganzer, N. Heinrich, K. R. Müller, Machine Learning Models for Lipophilicity and their Domain of Applicability
Mol. Pharm., 4(4):524-538, 2007 [bibtex] [pdf] [url]

T. Schroeter, A. Schwaighofer, S. Mika, A. T. Laak, D. Suelzle, U. Ganzer, N. Heinrich, K. R. Müller, Estimating the Domain of Applicability for Machine Learning QSAR RModels: A Study on Aqueous Solubility of Drug Discovery Molecules
Journal of Computer Aided Molecular Design - regular issue, 21(12):651-664, 2007 [bibtex] [pdf] [url]

A. Schwaighofer, T. Schroeter, S. Mika, J. Laub, A. t. Laak, D. Sülzle, U. Ganzer, N. Heinrich, K. R. Müller, Accurate Solubility Prediction with Error Bars for Electrolytes: A Machine Learning Approach
Journal of Chemical Information and Modelling, 47(2):407-424, 2007 [bibtex] [pdf] [url]

S. Sonnenburg, M. Braun, C. S. Ong, S. Bengio, L. Bottou, G. H. LeCun, K. R. Müller, F. Pereira, C. E. Rasmussen, G. Rätsch, B. Schölkopf, A. Smola, P. Vincent, J. Weston, R. Williamson, The Need for Open Source Software in Machine Learning
Journal of Machine Learning Research, 8:2443-2466, 2007 [bibtex] [pdf]

M. Sugiyama, M. Krauledat, K. R. Müller, Covariate Shift Adaptation by Importance Weighted Cross Validation
Journal of Machine Learning Research, 8:1027-1061, 2007 [bibtex] [pdf]

Book chapters

B. Blankertz, G. Dornhege, M. Krauledat, V. Kunzmann, F. Losch, G. Curio, K. R. Müller, The Berlin Brain-Computer Interface: Machine-Learning based Detection of User Specific Brain States
Toward Brain-Computer Interfacing, MIT press, 2007 [bibtex]

G. Dornhege, M. Krauledat, K. R. Müller, B. Blankertz, General signal processing and machine learning tools for BCI
Toward Brain-Computer Interfacing, MIT Press, 2007 [bibtex]

A. Kübler, K. R. Müller, An introducton to brain computer interfacing
Toward Brain-Computer Interfacing, MIT press, 2007 [bibtex]

J. Kohlmorgen, G. Dornhege, M. Braun, B. Blankertz, K. R. Müller, G. Curio, K. Hagemann, A. Bruns, M. Schrauf, W. Kincses, Improving human performance in a real operating environment through real-time mental workload detection
Toward Brain-Computer Interfacing, MIT press, 2007 [bibtex] [pdf]

M. Krauledat, P. Shenoy, B. Blankertz, R. P. Rao, K. R. Müller, Adaptation in CSP-based BCI systems
Toward Brain-Computer Interfacing, MIT Press, 2007 [bibtex]

Conference papers

B. Blankertz, M. Krauledat, G. Dornhege, J. Williamson, R. Murray-Smith, K. R. Müller, A Note on Brain Actuated Spelling with the Berlin Brain-Computer Interface
Universal Access in HCI, Part II, HCII 2007, Springer, LNCS, 4555:759-768, 2007 [bibtex] [pdf]

M. L. Braun, J. Buhmann, K. R. Müller, Denoising and Dimension Reduction in Feature Space, accepted
Advances in Neural Inf. Proc. Systems (NIPS 20), 2007 [bibtex]

M. Krauledat, M. Schröder, B. Blankertz, K. R. Müller, Reducing Calibration Time For Brain-Computer Interfaces: A Clustering Approach
Advances in Neural Information Processing Systems 19, MIT Press, 2007 [bibtex] [pdf]

K. R. Müller, M. Krauledat, G. Dornhege, G. Curio, B. Blankertz, Machine Learning and Applications for Brain-Computer Interfacing
Human Interface, Part I, HCII 2007, Springer, LNCS, 4557:705-714, 2007 [bibtex]

R. Tomioka, K. Aihara, K. R. Müller, Logistic Regression for Single Trial EEG Classification
Advances in Neural Information Processing Systems 19, MIT Press, 2007 [bibtex] [pdf]

2006

Journal papers

G. Blanchard, M. Sugiyama, M. Kawanabe, V. Spokoiny, K. R. Müller, In search of non-Gaussian components of a high-dimensional distribution
Journal of Machine Learning Research, 7:247-282, 2006 [bibtex] [pdf]

B. Blankertz, G. Dornhege, M. Krauledat, K. R. Müller, V. Kunzmann, F. Losch, G. Curio, The Berlin Brain-Computer Interface: EEG-based communication without subject training
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society, 14(2):147-152, 2006 [bibtex] [pdf] [url]

B. Blankertz, G. Dornhege, S. Lemm, M. Krauledat, G. Curio, K. R. Müller, The Berlin Brain-Computer Interface: Machine Learning Based Detection of User Specific Brain States
J Universal Computer Sci, 12(6):581-607, 2006 [bibtex] [pdf] [url]

B. Blankertz, K. R. Müller, D. Krusienski, G. Schalk, J. R. Wolpaw, A. Schlögl, G. Pfurtscheller, J. d. R. Millán, M. Schröder, N. Birbaumer, The BCI Competition III: Validating Alternative Approachs to Actual BCI Problems
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society, 14(2):153-159, 2006 [bibtex] [pdf] [url]

G. Dornhege, B. Blankertz, M. Krauledat, F. Losch, G. Curio, K. R. Müller, Combined optimization of spatial and temporal filters for improving Brain-Computer Interfacing
IEEE transactions on bio-medical engineering, 53(11):2274-2281, 2006 [bibtex] [pdf] [url]

S. Harmeling, G. Dornhege, D. Tax, F. C. Meinecke, K. R. Müller, From outliers to prototypes: ordering data
Neurocomputing, 69(13-15):1608-1618, 2006 [bibtex]

P. Laskov, C. Gehl, S. Krüger, K. R. Müller, Incremental Support Vector Learning: Analysis, Implementation and Applications
Journal of Machine Learning Research, 7:1909-1936, 2006 [bibtex] [pdf]

J. Laub, V. Roth, J. Buhmann, K. R. Müller, On the information and representation of non-Euclidean pairwise data
Pattern Recognition, 39(10):1815-1826, 2006 [bibtex]

S. Lemm, G. Curio, Y. Hlushchuk, K. R. Müller, Enhancing the Signal to Noise Ratio of ICA-based Extracted ERPs
IEEE transactions on bio-medical engineering, 53(4):601-607, 2006 [bibtex]

K. R. Müller, B. Blankertz, Toward noninvasive Brain-Computer Interfaces
IEEE Signal Processing Magazine, 23(5):125-128, 2006 [bibtex] [pdf] [url]

D. J. McFarland, C. W. Anderson, K. R. Müller, A. Schlögl, D. J. Krusienski, BCI Meeting 2005-workshop on BCI signal processing: feature extraction and translation
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society, 14:135-138, 2006 [bibtex] [url]

G. Nolte, F. C. Meinecke, A. Ziehe, K. R. Müller, Identifying interactions in mixed and noisy complex systems
Physical Review E, 73:051913, 2006 [bibtex]

P. Shenoy, M. Krauledat, B. Blankertz, R. P. Rao, K. R. Müller, Towards Adaptive Classification for BCI
Journal of neural engineering, 3(1):R13-R23, 2006 [bibtex] [pdf] [url]

Book chapters

N. Hill, T. N. Lal, M. Schröder, T. Hinterberger, G. Widman, C. E. Elger, B. Schölkopf, N. Birbaumer, Classifying Event-Related Desynchronization in EEG, ECoG and MEG Signals
Pattern Recognition, Springer Berlin Heidelberg, Lecture Notes in Computer Science, 4174:404-413, 2006 [bibtex] [url]

Conference papers

G. Blanchard, M. Sugiyama, M. Kawanabe, V. Spokoiny, K. R. Müller, Non-Gaussian component analysis: a semi-parametric framework for linear dimension reduction
Advances in Neural Inf. Proc. Systems (NIPS 05), 18, 2006 [bibtex] [pdf]

B. Blankertz, G. Dornhege, M. Krauledat, M. Schröder, J. Williamson, R. Murray-Smith, K. R. Müller, The Berlin Brain-Computer Interface presents the novel mental typewriter Hex-o-Spell
Proceedings of the 3rd International Brain-Computer Interface Workshop and Training Course 2006, Verlag der TU Graz, 2006 [bibtex] [pdf]

G. Dornhege, B. Blankertz, M. Krauledat, F. Losch, G. Curio, K. R. Müller, Optimizing spatio-temporal filters for improving Brain-Computer Interfacing
Advances in Neural Inf. Proc. Systems (NIPS 05), MIT Press, 18:315-322, 2006 [bibtex]

M. Kawanabe, G. Blanchard, M. Sugiyama, V. Spokoiny, K. R. Müller, A novel dimension reduction procedure for searching non-Gaussian subspaces, accepted
Proc. of ICA2006, 2006 [bibtex]

M. Krauledat, B. Blankertz, G. Dornhege, M. Schröder, G. Curio, K. R. Müller, On-line differentiation of neuroelectric activities: algorithms and applications
Proceedings of the 28th Annual International Conference IEEE EMBS on Biomedicine, 2006 [bibtex] [pdf]

K. R. Müller, M. Krauledat, G. Dornhege, S. Jähnichen, G. Curio, B. Blankertz, A note on the Berlin Brain-Computer Interface
Human Interaction with Machines: Proceedings of the 6th International Workshop held at the Shanghai Jiao Tong University, 2006 [bibtex]

G. Nolte, A. Ziehe, F. C. Meinecke, K. R. Müller, Analyzing Coupled Brain Sources: Distinguishing True from Spurious Interaction, accepted
Advances in Neural Inf. Proc. Systems (NIPS 05), 18, 2006 [bibtex]

F. Popescu, Y. Badower, S. Fazli, G. Dornhege, K. R. Müller, EEG-based control of reaching to visual targets
Dynamical Principles for neuroscience and intelligent biomimetic devices - Abstracts of the EPFL-LATSIS Symposium 2006, 2006 [bibtex]

K. Rieck, P. Laskov, K. R. Müller, Efficient Algorithms for Similarity Measures over Sequential Data: A Look beyond Kernels
Pattern Recognition, Proc. of 28th DAGM Symposium, 2006 [bibtex] [pdf]

M. Sugiyama, M. Kawanabe, G. Blanchard, V. Spokoiny, K. R. Müller, Obtaining the best linear unbiased estimator of noisy signals by non-Gaussian component analysis
Proc. of ICASSP2006, 2006 [bibtex]

2005

Journal papers

M. Kawanabe, K. R. Müller, Estimating functions for blind separation when sources have variance dependencies
Journal of Machine Learning Research, 6:453-482, 2005 [bibtex]

S. Lemm, B. Blankertz, G. Curio, K. R. Müller, Spatio-Spectral Filters for Improving Classification of Single Trial EEG
IEEE transactions on bio-medical engineering, 52(9):1541-1548, 2005 [bibtex] [pdf] [url]

K. R. Müller, G. Rätsch, S. Sonnenburg, S. Mika, M. Grimm, N. Heinrich, Classifying 'Drug-likeness' with Kernel-Based Learning Methods
J. Chem. Inf. Model, 45:249-253, 2005 [bibtex] [pdf]

F. C. Meinecke, S. Harmeling, K. R. Müller, Inlier-based ICA with an application to super-imposed images
International Journal of Imaging Systems and Technology, Wiley Subscription Services, Inc., A Wiley Company, 15(1):48-55, 2005 [bibtex] [url]

F. C. Meinecke, A. Ziehe, J. Kurths, K. R. Müller, Measuring Phase Synchronization of Superimposed Signals
Physical Review Letters, 94(8):084102, 2005 [bibtex] [pdf]

C. Schäfer, J. Schräpler, K. R. Müller, G. G. Wagner, Automatic Identification of Faked and Fraudulent Interviews in the German SOEP
Schmollers Jahrbuch,Duncker & Humblot, Berlin, 125:183-193, 2005 [bibtex]

S. Sugiyama, K. R. Müller, Input-Dependent Estimation of Generalization Error under Covariate Shift
Statistics and Decisions, 23(4):249-279, 2005 [bibtex] [pdf]

Conference papers

P. Laskov, K. Rieck, C. Schäfer, K. R. Müller, Visualization of anomaly detection using prediction sensitivity
Proc. of Conference "Sicherheit, Schutz und Zuverlässigkeit" (SICHERHEIT), 2005 [bibtex] [pdf]

Technical reports

B. Blankertz, G. Dornhege, M. Krauledat, K. R. Müller, G. Curio, The Berlin Brain-Computer Interface: Report from the Feedback Sessions
Fraunhofer FIRST, 2005 [bibtex] [pdf]

2004

Journal papers

B. Blankertz, K. R. Müller, G. Curio, T. M. Vaughan, G. Schalk, J. R. Wolpaw, A. Schlögl, C. Neuper, G. Pfurtscheller, T. Hinterberger, M. Schröder, N. Birbaumer, The BCI Competition 2003: Progress and Perspectives in Detection and Discrimination of EEG Single Trials
IEEE transactions on bio-medical engineering, 51(6):1044-1051, 2004 [bibtex] [pdf] [url]

G. Dornhege, B. Blankertz, G. Curio, K. R. Müller, Boosting bit rates in non-invasive EEG single-trial classifications by feature combination and multi-class paradigms
IEEE transactions on bio-medical engineering, 51(6):993-1002, 2004 [bibtex] [pdf] [url]

S. Harmeling, F. C. Meinecke, K. R. Müller, Injecting noise for analysing the stability of ICA components
Signal Processing, 84:255-266, 2004 [bibtex]

M. Krauledat, G. Dornhege, B. Blankertz, G. Curio, K. R. Müller, The Berlin Brain-Computer Interface For Rapid Response
Biomed Tech, 49(1):61-62, 2004 [bibtex] [pdf]

P. Laskov, C. Schäfer, I. Kotenko, K. R. Müller, Intrusion detection in unlabeled data with quarter-sphere Support Vector Machines (Extended Version)
Praxis der Informationsverarbeitung und Kommunikation, 27:228-236, 2004 [bibtex]

J. Laub, K. R. Müller, Feature Discovery in Non-Metric Pairwise Data
Journal of Machine Learning, 5(Jul):801-818, 2004 [bibtex]

K. R. Müller, M. Krauledat, G. Dornhege, G. Curio, B. Blankertz, Machine learning techniques for Brain-Computer Interfaces
Biomed Tech, 49(1):11-22, 2004 [bibtex] [pdf]

K. R. Müller, R. Vigario, F. C. Meinecke, A. Ziehe, Blind Source Separation Techniques For Decomposing Event-Related Brain Signals
International Journal of Bifurcation and Chaos, 14(2):773-791, 2004 [bibtex]

M. Sugiyama, M. Kawanabe, K. R. Müller, Trading Variance Reduction with Unbiasedness: The Regularized Subspace Information Criterion for Robust Model Selection in Kernel Regression
Neural Computation, 16(5):1077-1104, 2004 [bibtex] [pdf]

K. Tsuda, S. Akaho, M. Kawanabe, K. R. Müller, Asymptotic properties of the Fisher kernel
Neural Computation, 16:115-137, 2004 [bibtex]

A. Ziehe, P. Laskov, G. Nolte, K. R. Müller, A Fast Algorithm for Joint Diagonalization with Non-orthogonal Transformations and its Application to Blind Source Separation
Journal of Machine Learning Research, 5:777-800, 2004 [bibtex] [pdf]

Book chapters

S. Mika, C. Schäfer, P. Laskov, D. Tax, K. R. Müller, Support Vector Machines
Handbook of Computational Statistics, Springer, Berlin, 2004 [bibtex]

Conference papers

G. Dornhege, B. Blankertz, G. Curio, K. R. Müller, Increase Information Transfer Rates in BCI by CSP Extension to Multi-class
Advances in Neural Information Processing Systems, MIT Press, 16:733-740, 2004 [bibtex] [pdf]

M. Kawanabe, K. R. Müller, Estimating functions for blind separation when sources have variance-dependencies, accepted
Proc. of ICA2004, 2004 [bibtex] [pdf]

M. Krauledat, G. Dornhege, B. Blankertz, F. Losch, G. Curio, K. R. Müller, Improving Speed And Accuracy Of Brain-Computer Interfaces Using Readiness Potential Features
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, 4:4511-4515, 2004 [bibtex] [pdf] [url]

F. C. Meinecke, S. Harmeling, K. R. Müller, Robust ICA for Super-Gaussian Sources
Proc. Int. Workshop on Independent Component Analysis and Blind Signal Separation (ICA2004), 2004 [bibtex] [pdf]

A. Yeredor, A. Ziehe, K. R. Müller, Approximate joint diagonalization using a natural-gradient approach, Proc. ICA 2004
Lecture Notes in Computer Science, Springer-Verlag, 3195:89-96, 2004 [bibtex]

2003

Journal papers

B. Blankertz, G. Dornhege, C. Schäfer, R. Krepki, J. Kohlmorgen, K. R. Müller, V. Kunzmann, F. Losch, G. Curio, Boosting Bit Rates and Error Detection for the Classification of Fast-Paced Motor Commands Based on Single-Trial EEG Analysis
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society, 11(2):127-131, 2003 [bibtex] [pdf] [url]

S. Harmeling, A. Ziehe, M. Kawanabe, K. R. Müller, Kernel-based Nonlinear Blind Source Separation
Neural Computation, 15:1089-1124, 2003 [bibtex]

K. R. Müller, C. W. Anderson, G. E. Birch, Linear and Non-Linear Methods for Brain-Computer Interfaces
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society, 11(2):165-169, 2003 [bibtex] [pdf]

S. Mika, G. Rätsch, J. Weston, B. Schölkopf, A. Smola, K. R. Müller, Constructing Descriptive and Discriminative Non-Linear Features: Rayleigh Coefficients in Kernel Feature Spaces
IEEE Transaction on Pattern Analysis and Machine Intelligence, 25(5):623-628, 2003 [bibtex]

S. Mika, G. Rätsch, J. Weston, B. Schölkopf, A. J. Smola, K. R. Müller, Learning discriminative and invariant nonlinear features
IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(5):623-628, 2003 [bibtex]

P. Sajda, A. Gerson, K. R. Müller, B. Blankertz, L. Parra, A Data Analysis Competition to Evaluate Machine Learning Algorithms for use in Brain-Computer Interfaces
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society, 11(2):184-185, 2003 [bibtex] [pdf] [url]

A. Ziehe, M. Kawanabe, S. Harmeling, K. R. Müller, Blind separation of post-nonlinear mixtures using linearizing transformations and temporal decorrelation
Journal of Machine Learning Research, 4:1319-1338, 2003 [bibtex] [pdf]

Conference papers

G. Dornhege, B. Blankertz, G. Curio, K. R. Müller, Combining Features for BCI
Advances in Neural Inf. Proc. Systems (NIPS 02), 15:1115-1122, 2003 [bibtex] [pdf]

S. Harmeling, F. C. Meinecke, K. R. Müller, Analysing ICA components by injecting noise
Proc. Int. Workshop on Independent Component Analysis and Blind Signal Separation (ICA2003), 2003 [bibtex] [pdf]

R. Krepki, B. Blankertz, G. Curio, K. R. Müller, The Berlin Brain-Computer Interface (BBCI): towards a new communication channel for online control of multimedia applications and computer games
9th International Conference on Distributed Multimedia Systems (DMS'03), 2003 [bibtex] [pdf]

V. Roth, J. Laub, J. Buhmann, K. R. Müller, Going metric: Denoising pairwise data
Advances in Neural Information Processing 15, MIT Press, 2003 [bibtex]

D. Tax, K. R. Müller, Feature extraction for one-class classification
ICANN/ICONIP, 2003 [bibtex] [pdf]

K. Tsuda, M. Kawanabe, K. R. Müller, Clustering with the Fisher score
Advances in Neural Information Processing 15, MIT Press, 2003 [bibtex]

A. Ziehe, M. Kawanabe, S. Harmeling, K. R. Müller, Blind Separation of Post-Nonlinear Mixtures using Gaussianizing Transformations and Temporal Decorrelation
Proc. 4th International Symposium on Independent Component Analysis and Blind Signal Separation (ICA2003), 2003 [bibtex]

A. Ziehe, P. Laskov, K. R. Müller, G. Nolte, A Linear Least-Squares Algorithm for Joint Diagonalization
Proc. 4th International Symposium on Independent Component Analysis and Blind Signal Separation (ICA2003), 2003 [bibtex]

2002

Journal papers

F. C. Meinecke, A. Ziehe, M. Kawanabe, K. R. Müller, A Resampling Approach to Estimate the Stability of one- or multidimensional Independent Components
IEEE transactions on bio-medical engineering, 49(12):1514-1525, 2002 [bibtex] [pdf]

N. Murata, M. Kawanabe, A. Ziehe, K. R. Müller, S. Amari, On-line learning in changing environments with applications in supervised and unsupervised learning
Neural Networks, 15(4-6):743-760, 2002 [bibtex]

G. Rätsch, S. Mika, B. Schölkopf, K. R. Müller, Constructing Boosting Algorithms from SVMs: An Application to One-Class Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(9):1184-1199, 2002 [bibtex] [pdf]

M. Sugiyama, K. R. Müller, The Subspace Information Criterion for Infinite Dimensional Hypothesis Spaces
Journal of Machine Learning Research, 3(Nov):323-359, 2002 [bibtex] [pdf]

K. Tsuda, M. Kawanabe, G. Rätsch, S. Sonnenburg, K. R. Müller, A New Discriminative Kernel from Probabilistic Models
Neural Computation, 14:2397-2414, 2002 [bibtex] [pdf] [ps]

K. Tsuda, M. Sugiyama, K. R. Müller, Subspace Information Criterion for Non-Quadratic Regularizers - Model Selection for Sparse Regressors
IEEE Transactions on Neural Networks, 13(1):70-80, 2002 [bibtex] [pdf]

K. Tsuda, M. Sugiyama, K. R. Müller, Subspace Information Criterion for Sparse Regressors, in Japanese
IEICE Transactions, 85-D-II(5):766-775, 2002 [bibtex] [pdf]

Conference papers

B. Blankertz, G. Curio, K. R. Müller, Classifying Single Trial EEG: Towards Brain Computer Interfacing
Advances in Neural Inf. Proc. Systems (NIPS 01), 14:157-164, 2002 [bibtex] [pdf]

S. Harmeling, A. Ziehe, M. Kawanabe, K. R. Müller, Kernel feature spaces and Nonlinear blind source separation
Advances in Neural Information Processing Systems, MIT Press, 14, 2002 [bibtex] [pdf]

F. C. Meinecke, A. Ziehe, M. Kawanabe, K. R. Müller, Estimating the Reliability of ICA Projections
Advances in Neural Information Processing Systems 14, MIT Press, 2002 [bibtex] [pdf]

S. Sonnenburg, G. Rätsch, A. Jagota, K. R. Müller, New Methods for Splice-Site Recognition, Copyright by Springer
In Proceedings of the International Conference on Artifical Neural Networks., 2002 [bibtex] [pdf] [ps]

M. Sugiyama, K. R. Müller, Selecting Ridge Parameters in Infinite Dimensional Hypothesis Spaces
Artificial Neural Networks, Springer, Lecture Notes in Computer Science, 2415:528-534, 2002 [bibtex] [pdf]

K. Tsuda, M. Kawanabe, G. Rätsch, S. Sonnenburg, K. R. Müller, A New Discriminative Kernel from Probabilistic Models
Advances in Neural information processings systems, 14, 2002 [bibtex] [pdf] [ps]

R. Vigário, A. Ziehe, K. R. Müller, J. Särelä, E. Oja, V. Jousmäki, G. Wübbeler, L. Trahms, B. Mackert, G. Curio, Blind decomposition of multimodal and DC evoked responses, ISBN 0-262-19481-3
Advances in Exploratory analysis and data modeling in functional neuroimaging, MIT Press, Cambridge MA., 2002 [bibtex]

Technical reports

S. Harmeling, A. Ziehe, M. Kawanabe, K. R. Müller, Kernel-based Nonlinear Blind Source Separation
BLISS project, 2002 [bibtex]

2001

Journal papers

K. R. Müller, S. Mika, G. Rätsch, K. Tsuda, B. Schölkopf, An Introduction to Kernel-based Learning Algorithms
IEEE Neural Networks, 12(2):181-201, 2001 [bibtex]

G. Nolte, A. Ziehe, K. R. Müller, Noise robust estimates of correlation dimension and $K_2$ entropy, PACS: 02.50.-r, 05.45.Tp, 05.45.Ac
Phys.rev.E, 64(1):016112, 2001 [bibtex]

T. Onoda, G. Rätsch, K. R. Müller, An Arcing algorithm with an intuitive learning control parameter, in Japanese, a similar version in english appeared in Advances in Large Margin Classifiers
Journal of the Japanese Society for AI, 16(5C):417-426, 2001 [bibtex] [pdf]

G. Rätsch, T. Onoda, K. R. Müller, Soft Margins for AdaBoost
Machine Learning, Kluwer Academic Publishers, 42(3):287-320, 2001 [bibtex]

Conference papers

S. Harmeling, A. Ziehe, M. Kawanabe, B. Blankertz, K. R. Müller, Nonlinear blind source separation using kernel feature spaces
Proc. Int. Workshop on Independent Component Analysis and Blind Signal Separation (ICA2001), 2001 [bibtex] [pdf]

F. C. Meinecke, A. Ziehe, M. Kawanabe, K. R. Müller, Assessing reliability of ICA projections - a resampling approach
Proc. Int. Workshop on Independent Component Analysis and Blind Signal Separation (ICA2001), 2001 [bibtex] [pdf]

S. Mika, G. Rätsch, K. R. Müller, A mathematical programming approach to the Kernel Fisher algorithm
Advances in Neural Information Processing Systems, MIT Press, 13:591-597, 2001 [bibtex] [pdf]

K. Tsuda, G. Rätsch, S. Mika, K. R. Müller, Learning To Predict the Leave-one-out Error of Kernel based classifiers
Proc. ICANN'01, 2001 [bibtex] [pdf]

A. Ziehe, M. Kawanabe, S. Harmeling, K. R. Müller, Separation of post-nonlinear mixtures using ACE and temporal decorrelation
Proc. Int. Workshop on Independent Component Analysis and Blind Signal Separation (ICA2001), 2001 [bibtex]

A. Ziehe, G. Nolte, T. Sander, K. R. Müller, G. Curio, A comparison of ICA-based artifact reduction methods for MEG
Recent Advances in Biomagnetism, Proc. of the 12th International conference on Biomagnetism, Helsinki University of Technology, 2001 [bibtex] [pdf]

2000

Books

S. Solla, T. Leen, K. R. Müller, Advances in Neural Information Processing System 12 (NIPS'99)
MIT Press, 2000 [bibtex]

Journal papers

J. Kohlmorgen, K. R. Müller, J. Rittweger, K. Pawelzik, Identification of Nonstationary Dynamics in Physiological Recordings, The original publication is available on LINK at http://link.springer.de.
Biological cybernetics, Springer, 83(1):73-84, 2000 [bibtex] [pdf]

S. Liehr, K. Pawelzik, J. Kohlmorgen, S. Lemm, K. R. Müller, Prediction of Financial Data with Hidden Markov Mixtures of Experts
Int. Journal of Theoretical and Applied Finance, World Scientific, 3(3):593, 2000 [bibtex]

T. Onoda, G. Rätsch, K. R. Müller, An asymptotical Analysis and Improvement of AdaBoost in the binary classification case, In japanese
Journal of the Japanese Society for AI, 15(2):287-296, 2000 [bibtex]

G. Wübbeler, A. Ziehe, B. Mackert, K. R. Müller, L. Trahms, G. Curio, Independent Component Analysis of Non-invasively Recorded Cortical Magnetic DC-fields in Humans
IEEE Transactions on Biomedical Engineering, 47(5):594-599, 2000 [bibtex]

A. Ziehe, K. R. Müller, G. Nolte, B. Mackert, G. Curio, Artifact reduction in magnetoneurography based on time-delayed second-order correlations
IEEE transactions on bio-medical engineering, 47(1):75-87, 2000 [bibtex]

A. Zien, G. Rätsch, S. Mika, B. Schölkopf, T. Lengauer, K. R. Müller, Engineering Support Vector Machine Kernels That Recognize Translation Initiation Sites in DNA
BioInformatics, 16(9):799-807, 2000 [bibtex] [pdf]

Book chapters

G. Rätsch, B. Schölkopf, A. Smola, S. Mika, T. Onoda, K. R. Müller, Robust Ensemble Learning, similarly appeared in the Journal of the Japanese Society of AI, 2001
Proc. of the NIPS*98 Workshop on Large Margin Classifiers: Advances in Large Margin Classifiers, MIT Press, 2000 [bibtex] [pdf]

Conference papers

J. Kohlmorgen, S. Lemm, G. Rätsch, K. R. Müller, Analysis of Nonstationary Time Series by Mixtures of Self-Organizing Predictors
Neural Networks for Signal Processing X, IEEE, 2000 [bibtex] [pdf]

K. R. Müller, J. Kohlmorgen, A. Ziehe, B. Blankertz, Decomposition Algorithms for Analysing Brain Signals
Adaptive Systems for Signal Processing, Communications and Control, 2000 [bibtex] [pdf] [url]

K. R. Müller, G. Rätsch, J. Kohlmorgen, A. Smola, B. Schölkpf, V. Vladimir, Time series prediction using support vector regression and neural networks
2nd International Sympsium on Frontiers of Time Series Modelling: Nonparametric Approach to Knowledge Diescovery, Instiute of mathematical statistics publication, 2000 [bibtex]

S. Mika, G. Rätsch, J. Weston, B. Schölkopf, A. Smola, K. R. Müller, Invariant Feature Extraction and Classification in Kernel Spaces
Proc. NIPS 12, MIT Press, 2000 [bibtex] [pdf]

T. Onoda, G. Rätsch, K. R. Müller, A Non-Intrusive Monitoring System for Household Electric Appliances with Inverters
Proc. of NC'2000, 2000 [bibtex] [pdf]

L. Parra, C. Spence, P. Sajda, A. Ziehe, K. R. Müller, Unmixing Hyperspectral Data
Advances in Neural Information Processing Systems, MIT Press, 12:942-948, 2000 [bibtex]

G. Rätsch, B. Schölkopf, A. Smola, S. Mika, T. Onoda, K. R. Müller, Robust Ensemble Learning for Data Mining, This is a short version of iteRaeSchSmoMikOnoMue00
Proceedings of PAKDD'2000, Lecture Notes in Artificial Intelligence, Springer, 2000 [bibtex] [pdf]

G. Rätsch, B. Schölkopf, A. Smola, K. R. Müller, T. Onoda, S. Mika, $u $-Arc: Ensemble Learning in the Presence of Outliers
Proc. NIPS 12, MIT Press, 2000 [bibtex] [pdf]

G. Rätsch, M. Warmuth, S. Mika, T. Onoda, S. Lemm, K. R. Müller, Barrier Boosting
Proc. COLT'00, Morgan Kaufmann, 2000 [bibtex] [pdf]

A. Ziehe, G. Nolte, G. Curio, K. R. Müller, OFI: Optimal filtering algorithms for Source Separation
ICA 2000, 2000 [bibtex]

Technical reports

G. Rätsch, B. Schölkopf, S. Mika, K. R. Müller, SVM and Boosting: One Class
GMD FIRST, 2000 [bibtex] [pdf]

1999

Journal papers

S. Liehr, K. Pawelzik, J. Kohlmorgen, K. R. Müller, Hidden Markov Mixtures of Experts with an Application to EEG Recordings from Sleep
Theory in Biosciences, 118(3-4):246-260, 1999 [bibtex] [pdf]

B. Schölkopf, S. Mika, C. Burges, P. Knirsch, K. R. Müller, G. Rätsch, A. Smola, Input Space vs. Feature Space in Kernel-Based Methods
IEEE transactions on neural networks / a publication of the IEEE Neural Networks Council, 10(5):1000-1017, 1999 [bibtex] [pdf]

Conference papers

T. Graepel, R. Herbrich, B. Schölkopf, A. Smola, P. Bartlett, K. R. Müller, K. Obermayer, R. Williamson, Classification on Proximity Data with LP-Machines
Proceedings of ICANN'99, IEE Press, 1:304-309, 1999 [bibtex]

J. Kohlmorgen, S. Lemm, K. R. Müller, S. Liehr, K. Pawelzik, Fast Change Point Detection in Switching Dynamics using a Hidden Markov Model of Prediction Experts
Artificial Neural Networks - ICANN '99, IEE, 1999 [bibtex] [pdf]

S. Liehr, K. Pawelzik, J. Kohlmorgen, S. Lemm, K. R. Müller, Hidden Markov Gating for Prediction of Change Points in Switching Dynamical Systems
ESANN '99: Proc. of the European Symposium on Artificial Neural Networks, D-Facto, 1999 [bibtex] [pdf]

S. Liehr, K. Pawelzik, J. Kohlmorgen, S. Lemm, K. R. Müller, Hidden Markov Mixtures of Experts for Prediction of Non-Stationary Dynamics
Neural Networks for Signal Processing IX, 1999 [bibtex] [pdf]

K. R. Müller, P. Philips, A. Ziehe, $JADE_TD$: Combining higher-order statistics and temporal information for blind source separation (with noise)
ICA '99, 1999 [bibtex]

S. Mika, G. Rätsch, J. Weston, B. Schölkopf, K. R. Müller, Fisher Discriminant Analysis with Kernels
Neural Networks for Signal Processing IX, IEEE, 1999 [bibtex] [pdf]

G. Rätsch, T. Onoda, K. R. Müller, Regularizing AdaBoost
Proc. NIPS 11, MIT Press, 1999 [bibtex] [pdf]

A. Ziehe, K. R. Müller, G. Nolte, B. Mackert, G. Curio, Artifact removal in magneto-neurographic recordings with ICA using temporal information
Recent Advances in Biomagnetism, Proc. of the 11th international conference on Biomagnetism, Tohoku University press, 1999 [bibtex]

A. Zien, G. Rätsch, S. Mika, C. L. B. Schölkopf, A. Smola, T. Lengauer, K. R. Mueller, Engineering Support Vector Machine Kernel That Recognize Translation Initiation Sites in DNA
Proceedings GCB'99, 1999 [bibtex] [pdf]

1998

Books

G. Orr, K. R. Müller, (Eds.), Neural Networks: Tricks of the Trade
Springer Heidelberg, LNCS, 1998 [bibtex]

Journal papers

J. Kohlmorgen, K. R. Müller, Data Set A is a Pattern Matching Problem
Neural Processing Letters, Kluwer Academic Publishers, 7(1):43-47, 1998 [bibtex] [pdf]

B. Schölkopf, A. Smola, K. R. Müller, Nonlinear component analysis as a kernel eigenvalue problem
Neural computation, 10(5):1299-1319, 1998 [bibtex]

Book chapters

T. Hies, A. Ziehe, U. Eysholdt, K. R. Müller, Independent Component Analysis (ICA) von mehrkanaligen EEG-Daten mittels temporaler Dekorrelation, ISBN 3-925218-63-7
Medizinische Physik '98, Deutsche Gesellschaft für medizinische Physik, 1998 [bibtex]

K. R. Müller, N. Murata, A. Ziehe, S. Amari, On-line learning in Switching and Drifting environments with application to blind source separation
Cambridge University Press, On-line learning in neural networks, 1998 [bibtex]

K. R. Müller, A. Smola, G. Rätsch, B. Schölkopf, J. Kohlmorgen, V. Vapnik, Using Support Vector Machines for Time Series Prediction
Advances in Kernel Methods - Support Vector Learning, Proc. of the NIPS Workshop on Support Vectors, MIT Press, 1998 [bibtex] [pdf]

Conference papers

J. Kohlmorgen, K. R. Müller, K. Pawelzik, Analysis of Drifting Dynamics with Neural Network Hidden Markov Models
Advances in Neural Information Processing Systems 10, MIT Press, 1998 [bibtex] [pdf]

T. Onoda, G. Rätsch, K. R. Müller, An asymptotic analysis of AdaBoost in the binary classification case
Proc. ICANN'98, 1998 [bibtex] [pdf]

G. Rätsch, T. Onoda, K. R. Müller, An improvement of AdaBoost to avoid overfitting
Proc. ICONIP, 1998 [bibtex] [pdf]

A. Ziehe, K. R. Müller, TDSEP - an efficient algorithm for blind separation using time structure
Proc. of the 8th International Conference on Artificial Neural Networks, ICANN'98, Springer Verlag, Perspectives in Neural Computing, 1998 [bibtex]

Technical reports

G. Rätsch, T. Onoda, K. R. Müller, Soft Margins for AdaBoost, to appear in Machine Learning
Royal Holloway College, 1998 [bibtex] [pdf]

A. Ziehe, K. R. Müller, G. Nolte, B. Mackert, G. Curio, Artifact Reduction in Magnetoneurography Based on Time-Delayed Second Order Correlations
GMD - German National Research Center for Information Technology, FIRST, GMD Report No. 31, 1998 [bibtex]

1997

Journal papers

S. Amari, N. Murata, K. R. Müller, M. Finke, H. Yang, Asymptotic Statistical Theory of Overtraining and Cross-Validation
IEEE transactions on neural networks / a publication of the IEEE Neural Networks Council, 8(5):985-996, 1997 [bibtex]

Book chapters

B. Schölkopf, A. Smola, K. R. Müller, Kernel principal component analysis
Artificial Neural Networks-ICANN'97, Springer, 1997 [bibtex]

Conference papers

J. Kohlmorgen, K. R. Müller, K. Pawelzik, Segmentation and Identification of Drifting Dynamical Systems
Neural Networks for Signal Processing VII, IEEE, 1997 [bibtex] [pdf]

J. Kohlmorgen, K. R. Müller, J. Rittweger, K. Pawelzik, Analysis of Wake/Sleep EEG with Competing Experts
Artificial Neural Networks - ICANN '97, Springer, 1997 [bibtex] [pdf]

K. R. Müller, A. Smola, G. Rätsch, B. Schölkopf, J. Kohlmorgen, V. Vapnik, Predicting Time Series with Support Vector Machines
Artificial Neural Networks - ICANN '97, Springer, LNCS, 1327:999-1004, 1997 [bibtex] [pdf]

Technical reports

K. Pawelzik, K. R. Müller, J. Kohlmorgen, Divisive Strategies for Predicting Non-Autonomous and Mixed Systems
GMD, 1997 [bibtex] [pdf]

1996

Journal papers

K. Pawelzik, J. Kohlmorgen, K. R. Müller, Annealed Competition of Experts for a Segmentation and Classification of Switching Dynamics
Neural Computation, 8:340-356, 1996 [bibtex] [pdf]

Conference papers

J. Kohlmorgen, K. R. Müller, K. Pawelzik, Analysis of Drifting Dynamics with Competing Predictors
Artificial Neural Networks - ICANN '96, Springer, 1996 [bibtex] [pdf]

K. Pawelzik, K. R. Müller, J. Kohlmorgen, Prediction of Mixtures
Artificial Neural Networks - ICANN '96, Springer, 1996 [bibtex] [pdf]

1995

Journal papers

K. R. Müller, J. Kohlmorgen, K. Pawelzik, Analysis of Switching Dynamics with Competing Neural Networks
IEICE Trans. on Fundamentals of Electronics, Communications and Computer Science, E78-A(10):1306-1315, 1995 [bibtex] [pdf]

Conference papers

J. Kohlmorgen, K. R. Müller, K. Pawelzik, Improving Short-Term Prediction with Competing Experts
Artificial Neural Networks - ICANN '95, EC2, 2:215-220, 1995 [bibtex] [pdf]

K. R. Müller, J. Kohlmorgen, J. Rittweger, K. Pawelzik, Analysing Physiological Data from the Wake-Sleep State Transition with Competing Predictors
NOLTA '95: Las Vegas Symposium on Nonlinear Theory and its Applications, 1995 [bibtex] [pdf]

1994

Conference papers

J. Kohlmorgen, K. R. Müller, K. Pawelzik, Competing Predictors Segment and Identify Switching Dynamics
Artificial Neural Networks - ICANN '94, Springer, 1994 [bibtex] [pdf]

K. R. Müller, J. Kohlmorgen, K. Pawelzik, Segmentation and Identification of Switching Dynamics with Competing Neural Networks
ICONIP '94: Proc. of the Int. Conf. on Neural Information Processing, 1994 [bibtex]

K. R. Müller, J. Kohlmorgen, K. Pawelzik, The Use of Competing Neural Networks for Segmentation and Identification of Switching Dynamics
NOLTA '94: Kagoshima Symposium on Nonlinear Theory and its Applications, 1994 [bibtex]