ei
Zhang, K., Hyvärinen, A.
Nonlinear functional causal models for distinguishing cause from effect
In Statistics and Causality: Methods for Applied Empirical Research, pages: 185-201, 8, 1st, (Editors: Wolfgang Wiedermann and Alexander von Eye), John Wiley & Sons, Inc., 2016 (inbook)
ei
Hohmann, M., Fomina, T., Jayaram, V., Widmann, N., Förster, C., Just, J., Synofzik, M., Schölkopf, B., Schöls, L., Grosse-Wentrup, M.
A cognitive brain–computer interface for patients with amyotrophic lateral sclerosis
In Brain-Computer Interfaces: Lab Experiments to Real-World Applications, 228(Supplement C):221-239, 8, Progress in Brain Research, (Editors: Damien Coyle), Elsevier, 2016 (incollection)
ei
Charpiat, G., Hofmann, M., Schölkopf, B.
Kernel methods in medical imaging
In Handbook of Biomedical Imaging, pages: 63-81, 4, (Editors: Paragios, N., Duncan, J. and Ayache, N.), Springer, Berlin, Germany, June 2015 (inbook)
ei
Janzing, D., Steudel, B., Shajarisales, N., Schölkopf, B.
Justifying Information-Geometric Causal Inference
In Measures of Complexity: Festschrift for Alexey Chervonenkis, pages: 253-265, 18, (Editors: Vovk, V., Papadopoulos, H. and Gammerman, A.), Springer, 2015 (inbook)
ei
Grosse-Wentrup, M., Schölkopf, B.
A Review of Performance Variations in SMR-Based Brain–Computer Interfaces (BCIs)
In Brain-Computer Interface Research, pages: 39-51, 4, SpringerBriefs in Electrical and Computer Engineering, (Editors: Guger, C., Allison, B. Z. and Edlinger, G.), Springer, 2013 (inbook)
ei
Schölkopf, B., Janzing, D., Peters, J., Sgouritsa, E., Zhang, K., Mooij, J.
Semi-supervised learning in causal and anticausal settings
In Empirical Inference, pages: 129-141, 13, Festschrift in Honor of Vladimir Vapnik, (Editors: Schölkopf, B., Luo, Z. and Vovk, V.), Springer, 2013 (inbook)
ei
Sra, S.
Tractable large-scale optimization in machine learning
In Tractability: Practical Approaches to Hard Problems, pages: 202-230, 7, (Editors: Bordeaux, L., Hamadi , Y., Kohli, P. and Mateescu, R. ), Cambridge University Press , 2013 (inbook)
ei
Seldin, Y., Schölkopf, B.
On the Relations and Differences between Popper Dimension, Exclusion Dimension and VC-Dimension
In Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik, pages: 53-57, 6, (Editors: Schölkopf, B., Luo, Z. and Vovk, V.), Springer, 2013 (inbook)
ps
Gall, J., Lempitsky, V.
Class-Specific Hough Forests for Object Detection
In Decision Forests for Computer Vision and Medical Image Analysis, pages: 143-157, 11, (Editors: Criminisi, A. and Shotton, J.), Springer, 2013 (incollection)
ei
Schölkopf, B., Smola, A.
Support Vector Machines and Kernel Algorithms
In Encyclopedia of Biostatistics (2nd edition), Vol. 8, 8, pages: 5328-5335, (Editors: P Armitage and T Colton), John Wiley & Sons, NY USA, 2005 (inbook)
ei
Wagemans, J., Wichmann, F., de Beeck, H.
Visual perception
I: Basic principles
In Handbook of Cognition, pages: 3-47, (Editors: Lamberts, K. , R. Goldstone), Sage, London, 2005 (inbook)
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