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Bernhard Schölkopf: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Matthias O. Franz, Bernhard Schölkopf, Philip Georg, Hanspeter A. Mallot, Heinrich H. Bülthoff
    Learning View Graphs for Robot Navigation. [Citation Graph (0, 0)][DBLP]
    Agents, 1997, pp:138-147 [Conf]
  2. Arthur Gretton, Olivier Bousquet, Alex J. Smola, Bernhard Schölkopf
    Measuring Statistical Dependence with Hilbert-Schmidt Norms. [Citation Graph (0, 0)][DBLP]
    ALT, 2005, pp:63-77 [Conf]
  3. Bernhard Schölkopf, Ralf Herbrich, Alex J. Smola
    A Generalized Representer Theorem. [Citation Graph (0, 0)][DBLP]
    COLT/EuroCOLT, 2001, pp:416-426 [Conf]
  4. Robert C. Williamson, Alex J. Smola, Bernhard Schölkopf
    Entropy Numbers of Linear Function Classes. [Citation Graph (0, 0)][DBLP]
    COLT, 2000, pp:309-319 [Conf]
  5. Gökhan H. Bakir, Arthur Gretton, Matthias O. Franz, Bernhard Schölkopf
    Multivariate Regression via Stiefel Manifold Constraints. [Citation Graph (0, 0)][DBLP]
    DAGM-Symposium, 2004, pp:262-269 [Conf]
  6. Matthias O. Franz, Younghee Kwon, Carl Edward Rasmussen, Bernhard Schölkopf
    Semi-supervised Kernel Regression Using Whitened Function Classes. [Citation Graph (0, 0)][DBLP]
    DAGM-Symposium, 2004, pp:18-26 [Conf]
  7. Matthias O. Franz, Bernhard Schölkopf, Hanspeter A. Mallot, Heinrich H. Bülthoff, Andreas Zell
    Navigation mit Schnappschüssen. [Citation Graph (0, 0)][DBLP]
    DAGM-Symposium, 1998, pp:421-428 [Conf]
  8. N. Jeremy Hill, Thomas Navin Lal, Michael Schröder 0002, Thilo Hinterberger, Guido Widman, Christian Erich Elger, Bernhard Schölkopf, Niels Birbaumer
    Classifying Event-Related Desynchronization in EEG, ECoG and MEG Signals. [Citation Graph (0, 0)][DBLP]
    DAGM-Symposium, 2006, pp:404-413 [Conf]
  9. Wolf Kienzle, Gökhan H. Bakir, Matthias O. Franz, Bernhard Schölkopf
    Efficient Approximations for Support Vector Machines in Object Detection. [Citation Graph (0, 0)][DBLP]
    DAGM-Symposium, 2004, pp:54-61 [Conf]
  10. Bernhard Schölkopf, Alex J. Smola, Phil Knirsch, Chris Burges
    Fast Approximation of Support Vector Kernel Expansions, and an Interpretation of Clustering as Approximation in Feature Spaces. [Citation Graph (0, 0)][DBLP]
    DAGM-Symposium, 1998, pp:125-132 [Conf]
  11. Dengyong Zhou, Bernhard Schölkopf
    Learning from Labeled and Unlabeled Data Using Random Walks. [Citation Graph (0, 0)][DBLP]
    DAGM-Symposium, 2004, pp:237-244 [Conf]
  12. Dengyong Zhou, Bernhard Schölkopf
    Regularization on Discrete Spaces. [Citation Graph (0, 0)][DBLP]
    DAGM-Symposium, 2005, pp:361-368 [Conf]
  13. Koji Tsuda, HyunJung Shin, Bernhard Schölkopf
    Fast protein classification with multiple networks. [Citation Graph (0, 0)][DBLP]
    ECCB/JBI, 2005, pp:65- [Conf]
  14. Wolf Kienzle, Bernhard Schölkopf
    Training Support Vector Machines with Multiple Equality Constraints. [Citation Graph (0, 0)][DBLP]
    ECML, 2005, pp:182-193 [Conf]
  15. Bernhard Schölkopf, Jason Weston, Eleazar Eskin, Christina S. Leslie, William Stafford Noble
    A Kernel Approach for Learning from almost Orthogonal Patterns. [Citation Graph (0, 0)][DBLP]
    ECML, 2002, pp:511-528 [Conf]
  16. Robert C. Williamson, Alex J. Smola, Bernhard Schölkopf
    Entropy Numbers, Operators and Support Vector Kernels. [Citation Graph (0, 0)][DBLP]
    EuroCOLT, 1999, pp:285-299 [Conf]
  17. Alex J. Smola, Robert C. Williamson, Sebastian Mika, Bernhard Schölkopf
    Regularized Principal Manifolds. [Citation Graph (0, 0)][DBLP]
    EuroCOLT, 1999, pp:214-229 [Conf]
  18. Alexander Zien, Gunnar Rätsch, Sebastian Mika, Bernhard Schölkopf, Christian Lemmen, Alex J. Smola, Thomas Lengauer, Klaus-Robert Müller
    Engineering Support Vector Machine Kerneis That Recognize Translation Initialion Sites. [Citation Graph (0, 0)][DBLP]
    German Conference on Bioinformatics, 1999, pp:37-43 [Conf]
  19. Volker Blanz, Bernhard Schölkopf, Heinrich H. Bülthoff, Chris Burges, Vladimir Vapnik, Thomas Vetter
    Comparison of View-Based Object Recognition Algorithms Using Realistic 3D Models. [Citation Graph (0, 0)][DBLP]
    ICANN, 1996, pp:251-256 [Conf]
  20. Hanspeter A. Mallot, Matthias O. Franz, Bernhard Schölkopf, Heinrich H. Bülthoff
    The View-Graph Approach to Visual Navigation and Spatial Memory. [Citation Graph (0, 0)][DBLP]
    ICANN, 1997, pp:751-756 [Conf]
  21. Klaus-Robert Müller, Alex J. Smola, Gunnar Rätsch, Bernhard Schölkopf, Jens Kohlmorgen, Vladimir Vapnik
    Predicting Time Series with Support Vector Machines. [Citation Graph (0, 0)][DBLP]
    ICANN, 1997, pp:999-1004 [Conf]
  22. Bernhard Schölkopf, Chris Burges, Vladimir Vapnik
    Incorporating Invariances in Support Vector Learning Machines. [Citation Graph (0, 0)][DBLP]
    ICANN, 1996, pp:47-52 [Conf]
  23. Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller
    Kernel Principal Component Analysis. [Citation Graph (0, 0)][DBLP]
    ICANN, 1997, pp:583-588 [Conf]
  24. Stan Z. Li, QingDong Fu, Lie Gu, Bernhard Schölkopf, Yimin Cheng, HongJiang Zhang
    Kernel Machine Based Learning for Multi-View Face Detection and Pose Estimation. [Citation Graph (0, 0)][DBLP]
    ICCV, 2001, pp:674-679 [Conf]
  25. Sami Romdhani, Philip H. S. Torr, Bernhard Schölkopf, Andrew Blake
    Computationally Efficient Face Detection. [Citation Graph (0, 0)][DBLP]
    ICCV, 2001, pp:695-700 [Conf]
  26. Jihun Ham, Daniel D. Lee, Sebastian Mika, Bernhard Schölkopf
    A kernel view of the dimensionality reduction of manifolds. [Citation Graph (0, 0)][DBLP]
    ICML, 2004, pp:- [Conf]
  27. Thomas Navin Lal, Michael Schröder 0002, N. Jeremy Hill, Hubert Preißl, Thilo Hinterberger, Jürgen Mellinger, Martin Bogdan, Wolfgang Rosenstiel, Thomas Hofmann, Niels Birbaumer, Bernhard Schölkopf
    A brain computer interface with online feedback based on magnetoencephalography. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:465-472 [Conf]
  28. Neil D. Lawrence, Bernhard Schölkopf
    Estimating a Kernel Fisher Discriminant in the Presence of Label Noise. [Citation Graph (0, 0)][DBLP]
    ICML, 2001, pp:306-313 [Conf]
  29. Alex J. Smola, Bernhard Schölkopf
    Sparse Greedy Matrix Approximation for Machine Learning. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:911-918 [Conf]
  30. Bernhard Schölkopf, Florian Steinke, Volker Blanz
    Object correspondence as a machine learning problem. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:776-783 [Conf]
  31. Sören Sonnenburg, Gunnar Rätsch, Bernhard Schölkopf
    Large scale genomic sequence SVM classifiers. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:848-855 [Conf]
  32. Christian Walder, Olivier Chapelle, Bernhard Schölkopf
    Implicit surface modelling as an eigenvalue problem. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:936-939 [Conf]
  33. Mingrui Wu, Bernhard Schölkopf, Gökhan H. Bakir
    Building Sparse Large Margin Classifiers. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:996-1003 [Conf]
  34. Dengyong Zhou, Jiayuan Huang, Bernhard Schölkopf
    Learning from labeled and unlabeled data on a directed graph. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:1036-1043 [Conf]
  35. Holger Fröhlich, Olivier Chapelle, Bernhard Schölkopf
    Feature Selection for Support Vector Machines by Means of Genetic Algorithms. [Citation Graph (0, 0)][DBLP]
    ICTAI, 2003, pp:142-148 [Conf]
  36. Athanassia Chalimourda, Bernhard Schölkopf, Alex J. Smola
    Choosing in Support Vector Regression with Different Noise Models: Theory and Experiments. [Citation Graph (0, 0)][DBLP]
    IJCNN (5), 2000, pp:199-204 [Conf]
  37. Karsten M. Borgwardt, Arthur Gretton, Malte J. Rasch, Hans-Peter Kriegel, Bernhard Schölkopf, Alexander J. Smola
    Integrating structured biological data by Kernel Maximum Mean Discrepancy. [Citation Graph (0, 0)][DBLP]
    ISMB (Supplement of Bioinformatics), 2006, pp:49-57 [Conf]
  38. Gunnar Rätsch, Sören Sonnenburg, Bernhard Schölkopf
    RASE: recognition of alternatively spliced exons in C.elegans. [Citation Graph (0, 0)][DBLP]
    ISMB (Supplement of Bioinformatics), 2005, pp:369-377 [Conf]
  39. Tobias Jung, Luis Herrera, Bernhard Schölkopf
    Long Term Prediction of Product Quality in a Glass Manufacturing Process Using a Kernel Based Approach. [Citation Graph (0, 0)][DBLP]
    IWANN, 2005, pp:960-967 [Conf]
  40. Jason Weston, Bernhard Schölkopf, Olivier Bousquet
    Joint Kernel Maps. [Citation Graph (0, 0)][DBLP]
    IWANN, 2005, pp:176-191 [Conf]
  41. Bernhard Schölkopf, Chris Burges, Vladimir Vapnik
    Extracting Support Data for a Given Task. [Citation Graph (0, 0)][DBLP]
    KDD, 1995, pp:252-257 [Conf]
  42. Joaquin Quiñonero Candela, Carl Edward Rasmussen, Fabian H. Sinz, Olivier Bousquet, Bernhard Schölkopf
    Evaluating Predictive Uncertainty Challenge. [Citation Graph (0, 0)][DBLP]
    MLCW, 2005, pp:1-27 [Conf]
  43. Bernhard Schölkopf, Alex J. Smola
    A Short Introduction to Learning with Kernels. [Citation Graph (0, 0)][DBLP]
    Machine Learning Summer School, 2002, pp:41-64 [Conf]
  44. Alex J. Smola, Bernhard Schölkopf
    Bayesian Kernel Methods. [Citation Graph (0, 0)][DBLP]
    Machine Learning Summer School, 2002, pp:65-117 [Conf]
  45. Gökhan H. Bakir, Jason Weston, Bernhard Schölkopf
    Learning to Find Pre-Images. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  46. Dimitris Achlioptas, Frank McSherry, Bernhard Schölkopf
    Sampling Techniques for Kernel Methods. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:335-342 [Conf]
  47. Christopher J. C. Burges, Bernhard Schölkopf
    Improving the Accuracy and Speed of Support Vector Machines. [Citation Graph (0, 0)][DBLP]
    NIPS, 1996, pp:375-381 [Conf]
  48. Olivier Chapelle, Bernhard Schölkopf
    Incorporating Invariances in Non-Linear Support Vector Machines. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:609-616 [Conf]
  49. Olivier Chapelle, Jason Weston, Bernhard Schölkopf
    Cluster Kernels for Semi-Supervised Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:585-592 [Conf]
  50. Jan Eichhorn, Andreas S. Tolias, Alexander Zien, Malte Kuss, Carl Edward Rasmussen, Jason Weston, Nikos Logothetis, Bernhard Schölkopf
    Prediction on Spike Data Using Kernel Algorithms. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  51. Matthias O. Franz, Bernhard Schölkopf
    Implicit Wiener Series for Higher-Order Image Analysis. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  52. Paul Hayton, Bernhard Schölkopf, Lionel Tarassenko, Paul Anuzis
    Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:946-952 [Conf]
  53. N. Jeremy Hill, Thomas Navin Lal, Karin Bierig, Niels Birbaumer, Bernhard Schölkopf
    An Auditory Paradigm for Brain-Computer Interfaces. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  54. Wolf Kienzle, Gökhan H. Bakir, Matthias O. Franz, Bernhard Schölkopf
    Face Detection - Efficient and Rank Deficient. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  55. Thomas Navin Lal, Thilo Hinterberger, Guido Widman, Michael Schröder 0002, N. Jeremy Hill, Wolfgang Rosenstiel, Christian Erich Elger, Bernhard Schölkopf, Niels Birbaumer
    Methods Towards Invasive Human Brain Computer Interfaces. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  56. Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller
    Invariant Feature Extraction and Classification in Kernel Spaces. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:526-532 [Conf]
  57. Sebastian Mika, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller, Matthias Scholz, Gunnar Rätsch
    Kernel PCA and De-Noising in Feature Spaces. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:536-542 [Conf]
  58. Gunnar Rätsch, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller, Takashi Onoda, Sebastian Mika
    v-Arc: Ensemble Learning in the Presence of Outliers. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:561-567 [Conf]
  59. Bernhard Schölkopf
    The Kernel Trick for Distances. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:301-307 [Conf]
  60. Bernhard Schölkopf, Peter L. Bartlett, Alex J. Smola, Robert C. Williamson
    Shrinking the Tube: A New Support Vector Regression Algorithm. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:330-336 [Conf]
  61. Bernhard Schölkopf, Joachim Giesen, Simon Spalinger
    Kernel Methods for Implicit Surface Modeling. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  62. Bernhard Schölkopf, Patrice Simard, Alex J. Smola, Vladimir Vapnik
    Prior Knowledge in Support Vector Kernels. [Citation Graph (0, 0)][DBLP]
    NIPS, 1997, pp:- [Conf]
  63. Bernhard Schölkopf, Robert C. Williamson, Alex J. Smola, John Shawe-Taylor, John C. Platt
    Support Vector Method for Novelty Detection. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:582-588 [Conf]
  64. Alex J. Smola, Thilo-Thomas Frieß, Bernhard Schölkopf
    Semiparametric Support Vector and Linear Programming Machines. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:585-591 [Conf]
  65. Alex J. Smola, Bernhard Schölkopf
    From Regularization Operators to Support Vector Kernels. [Citation Graph (0, 0)][DBLP]
    NIPS, 1997, pp:- [Conf]
  66. Alex J. Smola, John Shawe-Taylor, Bernhard Schölkopf, Robert C. Williamson
    The Entropy Regularization Information Criterion. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:342-348 [Conf]
  67. Susanne Still, Bernhard Schölkopf, Klaus Hepp, Rodney J. Douglas
    Four-legged Walking Gait Control Using a Neuromorphic Chip Interfaced to a Support Vector Learning Algorithm. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:741-747 [Conf]
  68. Jason Weston, Olivier Chapelle, André Elisseeff, Bernhard Schölkopf, Vladimir Vapnik
    Kernel Dependency Estimation. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:873-880 [Conf]
  69. Felix A. Wichmann, Arnulf B. A. Graf, Eero P. Simoncelli, Heinrich H. Bülthoff, Bernhard Schölkopf
    Machine Learning Applied to Perception: Decision Images for Gender Classification. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  70. Dengyong Zhou, Olivier Bousquet, Thomas Navin Lal, Jason Weston, Bernhard Schölkopf
    Learning with Local and Global Consistency. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  71. Dengyong Zhou, Bernhard Schölkopf, Thomas Hofmann
    Semi-supervised Learning on Directed Graphs. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  72. Dengyong Zhou, Jason Weston, Arthur Gretton, Olivier Bousquet, Bernhard Schölkopf
    Ranking on Data Manifolds. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  73. Gunnar Rätsch, Bernhard Schölkopf, Alex J. Smola, Sebastian Mika, Takashi Onoda, Klaus-Robert Müller
    Robust Ensemble Learning for Data Mining. [Citation Graph (0, 0)][DBLP]
    PAKDD, 2000, pp:341-344 [Conf]
  74. Bernhard Schölkopf, Jason Weston, Eleazar Eskin, Christina S. Leslie, William Stafford Noble
    A Kernel Approach for Learning from Almost Orthogonal Patterns. [Citation Graph (0, 0)][DBLP]
    PKDD, 2002, pp:494-511 [Conf]
  75. Nello Cristianini, Bernhard Schölkopf
    Support Vector Machines and Kernel Methods: The New Generation of Learning Machines. [Citation Graph (0, 0)][DBLP]
    AI Magazine, 2002, v:23, n:3, pp:31-42 [Journal]
  76. Alex J. Smola, Bernhard Schölkopf
    On a Kernel-Based Method for Pattern Recognition, Regression, Approximation, and Operator Inversion. [Citation Graph (0, 0)][DBLP]
    Algorithmica, 1998, v:22, n:1/2, pp:211-231 [Journal]
  77. Matthias O. Franz, Bernhard Schölkopf, Hanspeter A. Mallot, Heinrich H. Bülthoff
    Learning View Graphs for Robot Navigation. [Citation Graph (0, 0)][DBLP]
    Auton. Robots, 1998, v:5, n:1, pp:111-125 [Journal]
  78. Jason Weston, Fernando Pérez-Cruz, Olivier Bousquet, Olivier Chapelle, André Elisseeff, Bernhard Schölkopf
    Feature selection and transduction for prediction of molecular bioactivity for drug design. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2003, v:19, n:6, pp:764-771 [Journal]
  79. Alexander Zien, Gunnar Rätsch, Sebastian Mika, Bernhard Schölkopf, Thomas Lengauer, Klaus-Robert Müller
    Engineering support vector machine kernels that recognize translation initiation sites. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2000, v:16, n:9, pp:799-807 [Journal]
  80. Bernhard Schölkopf, Klaus-Robert Müller, Alex J. Smola
    Lernen mit Kernen: Support-Vektor-Methoden zur Analyse hochdimensionaler Daten. [Citation Graph (0, 0)][DBLP]
    Inform., Forsch. Entwickl., 1999, v:14, n:3, pp:154-163 [Journal]
  81. Holger Fröhlich, Olivier Chapelle, Bernhard Schölkopf
    Feature Selection for Support Vector Machines Using Genetic Algorithms. [Citation Graph (0, 0)][DBLP]
    International Journal on Artificial Intelligence Tools, 2004, v:13, n:4, pp:791-800 [Journal]
  82. Matthias Hein, Olivier Bousquet, Bernhard Schölkopf
    Maximal margin classification for metric spaces. [Citation Graph (0, 0)][DBLP]
    J. Comput. Syst. Sci., 2005, v:71, n:3, pp:333-359 [Journal]
  83. Ulrike von Luxburg, Olivier Bousquet, Bernhard Schölkopf
    A Compression Approach to Support Vector Model Selection. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2004, v:5, n:, pp:293-323 [Journal]
  84. Alex J. Smola, Sebastian Mika, Bernhard Schölkopf, Robert C. Williamson
    Regularized Principal Manifolds. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2001, v:1, n:, pp:179-209 [Journal]
  85. Jason Weston, André Elisseeff, Bernhard Schölkopf, Michael E. Tipping
    Use of the Zero-Norm with Linear Models and Kernel Methods. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2003, v:3, n:, pp:1439-1461 [Journal]
  86. Arthur Gretton, Ralf Herbrich, Alexander J. Smola, Olivier Bousquet, Bernhard Schölkopf
    Kernel Methods for Measuring Independence. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2005, v:6, n:, pp:2075-2129 [Journal]
  87. Sören Sonnenburg, Gunnar Rätsch, Christin Schäfer, Bernhard Schölkopf
    Large Scale Multiple Kernel Learning. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1531-1565 [Journal]
  88. Mingrui Wu, Bernhard Schölkopf, Gökhan H. Bakir
    A Direct Method for Building Sparse Kernel Learning Algorithms. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:603-624 [Journal]
  89. Dennis DeCoste, Bernhard Schölkopf
    Training Invariant Support Vector Machines. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2002, v:46, n:1-3, pp:161-190 [Journal]
  90. Arnulf B. A. Graf, Felix A. Wichmann, Heinrich H. Bülthoff, Bernhard Schölkopf
    Classification of Faces in Man and Machine. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2006, v:18, n:1, pp:143-165 [Journal]
  91. Bernhard Schölkopf, John C. Platt, John Shawe-Taylor, Alex J. Smola, Robert C. Williamson
    Estimating the Support of a High-Dimensional Distribution. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2001, v:13, n:7, pp:1443-1471 [Journal]
  92. Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller
    Nonlinear Component Analysis as a Kernel Eigenvalue Problem. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1998, v:10, n:5, pp:1299-1319 [Journal]
  93. Bernhard Schölkopf, Alex J. Smola, Robert C. Williamson, Peter L. Bartlett
    New Support Vector Algorithms. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2000, v:12, n:5, pp:1207-1245 [Journal]
  94. Matthias O. Franz, Bernhard Schölkopf
    A Unifying View of Wiener and Volterra Theory and Polynomial Kernel Regression. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2006, v:18, n:12, pp:3097-3118 [Journal]
  95. Athanassia Chalimourda, Bernhard Schölkopf, Alex J. Smola
    Experimentally optimal v in support vector regression for different noise models and parameter settings. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2004, v:17, n:1, pp:127-141 [Journal]
  96. Athanassia Chalimourda, Bernhard Schölkopf, Alex J. Smola
    Experimentally optimal nu in support vector regression for different noise models and parameter settings. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2005, v:18, n:2, pp:205-0 [Journal]
  97. Alex J. Smola, Bernhard Schölkopf, Klaus-Robert Müller
    The connection between regularization operators and support vector kernels. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 1998, v:11, n:4, pp:637-649 [Journal]
  98. Kwang In Kim, Matthias O. Franz, Bernhard Schölkopf
    Iterative Kernel Principal Component Analysis for Image Modeling. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 2005, v:27, n:9, pp:1351-1366 [Journal]
  99. Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller
    Constructing Descriptive and Discriminative Nonlinear Features: Rayleigh Coefficients in Kernel Feature Spaces. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 2003, v:25, n:5, pp:623-633 [Journal]
  100. Gunnar Rätsch, Sebastian Mika, Bernhard Schölkopf, Klaus-Robert Müller
    Constructing Boosting Algorithms from SVMs: An Application to One-Class Classification. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 2002, v:24, n:9, pp:1184-1199 [Journal]
  101. Robert C. Williamson, Alex J. Smola, Bernhard Schölkopf
    Generalization performance of regularization networks and support vector machines via entropy numbers of compact operators. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 2001, v:47, n:6, pp:2516-2532 [Journal]
  102. Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola
    A Kernel Approach to Comparing Distributions. [Citation Graph (0, 0)][DBLP]
    AAAI, 2007, pp:1637-1641 [Conf]
  103. Alex J. Smola, Arthur Gretton, Le Song, Bernhard Schölkopf
    A Hilbert Space Embedding for Distributions. [Citation Graph (0, 0)][DBLP]
    ALT, 2007, pp:13-31 [Conf]
  104. Wolf Kienzle, Bernhard Schölkopf, Felix A. Wichmann, Matthias O. Franz
    How to Find Interesting Locations in Video: A Spatiotemporal Interest Point Detector Learned from Human Eye Movements. [Citation Graph (0, 0)][DBLP]
    DAGM-Symposium, 2007, pp:405-414 [Conf]
  105. Alexander J. Smola, Arthur Gretton, Le Song, Bernhard Schölkopf
    A Hilbert Space Embedding for Distributions. [Citation Graph (0, 0)][DBLP]
    Discovery Science, 2007, pp:40-41 [Conf]
  106. Mingrui Wu, Kai Yu, Shipeng Yu, Bernhard Schölkopf
    Local learning projections. [Citation Graph (0, 0)][DBLP]
    ICML, 2007, pp:1039-1046 [Conf]
  107. Xiaohai Sun, Dominik Janzing, Bernhard Schölkopf, Kenji Fukumizu
    A kernel-based causal learning algorithm. [Citation Graph (0, 0)][DBLP]
    ICML, 2007, pp:855-862 [Conf]
  108. Mingrui Wu, Bernhard Schölkopf
    A Local Learning Approach for Clustering. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:1529-1536 [Conf]
  109. Florian Steinke, Bernhard Schölkopf, Volker Blanz
    Learning Dense 3D Correspondence. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:1313-1320 [Conf]
  110. Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola
    A Kernel Method for the Two-Sample-Problem. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:513-520 [Conf]
  111. Dengyong Zhou, Jiayuan Huang, Bernhard Schölkopf
    Learning with Hypergraphs: Clustering, Classification, and Embedding. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:1601-1608 [Conf]
  112. Jiayuan Huang, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt, Bernhard Schölkopf
    Correcting Sample Selection Bias by Unlabeled Data. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:601-608 [Conf]
  113. Wolf Kienzle, Felix A. Wichmann, Bernhard Schölkopf, Matthias O. Franz
    A Nonparametric Approach to Bottom-Up Visual Saliency. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:689-696 [Conf]
  114. Christian Walder, Bernhard Schölkopf, Olivier Chapelle
    Implicit Surfaces with Globally Regularised and Compactly Supported Basis Functions. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:273-280 [Conf]
  115. Florian Steinke, Bernhard Schölkopf, Volker Blanz
    Support Vector Machines for 3D Shape Processing. [Citation Graph (0, 0)][DBLP]
    Comput. Graph. Forum, 2005, v:24, n:3, pp:285-294 [Journal]

  116. Towards Machine Learning of Motor Skills. [Citation Graph (, )][DBLP]


  117. Learning similarity measure for multi-modal 3D image registration. [Citation Graph (, )][DBLP]


  118. Markerless 3D Face Tracking. [Citation Graph (, )][DBLP]


  119. Automatic Image Colorization Via Multimodal Predictions. [Citation Graph (, )][DBLP]


  120. Distinguishing between cause and effect via kernel-based complexity measures for conditional distributions. [Citation Graph (, )][DBLP]


  121. Learning Inverse Dynamics: a Comparison. [Citation Graph (, )][DBLP]


  122. Automatic 3D face reconstruction from single images or video. [Citation Graph (, )][DBLP]


  123. Tailoring density estimation via reproducing kernel moment matching. [Citation Graph (, )][DBLP]


  124. Sparse multiscale gaussian process regression. [Citation Graph (, )][DBLP]


  125. Regression by dependence minimization and its application to causal inference in additive noise models. [Citation Graph (, )][DBLP]


  126. Detecting the direction of causal time series. [Citation Graph (, )][DBLP]


  127. Telling cause from effect based on high-dimensional observations. [Citation Graph (, )][DBLP]


  128. Movement templates for learning of hitting and batting. [Citation Graph (, )][DBLP]


  129. Multi-way set enumeration in real-valued tensors. [Citation Graph (, )][DBLP]


  130. Generalized Clustering via Kernel Embeddings. [Citation Graph (, )][DBLP]


  131. Kernel Measures of Conditional Dependence. [Citation Graph (, )][DBLP]


  132. An Analysis of Inference with the Universum. [Citation Graph (, )][DBLP]


  133. A Kernel Statistical Test of Independence. [Citation Graph (, )][DBLP]


  134. Characteristic Kernels on Groups and Semigroups. [Citation Graph (, )][DBLP]


  135. Nonlinear causal discovery with additive noise models. [Citation Graph (, )][DBLP]


  136. Diffeomorphic Dimensionality Reduction. [Citation Graph (, )][DBLP]


  137. Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance. [Citation Graph (, )][DBLP]


  138. Bayesian Experimental Design of Magnetic Resonance Imaging Sequences. [Citation Graph (, )][DBLP]


  139. An Empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence Analysis. [Citation Graph (, )][DBLP]


  140. A New Algorithm for Improving the Resolution of Cryo-EM Density Maps. [Citation Graph (, )][DBLP]


  141. Sparse online model learning for robot control with support vector regression. [Citation Graph (, )][DBLP]


  142. Where did I take that snapshot? Scene-based homing by image matching. [Citation Graph (, )][DBLP]


  143. Implicit Surface Modelling with a Globally Regularised Basis of Compact Support. [Citation Graph (, )][DBLP]


  144. Manifold-valued Thin-Plate Splines with Applications in Computer Graphics. [Citation Graph (, )][DBLP]


  145. Causal inference using the algorithmic Markov condition [Citation Graph (, )][DBLP]


  146. A Kernel Method for the Two-Sample Problem [Citation Graph (, )][DBLP]


  147. A note on integral probability metrics and $\phi$-divergences [Citation Graph (, )][DBLP]


  148. Causal Markov condition for submodular information measures [Citation Graph (, )][DBLP]


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