Bernhard Schölkopf

Manuel Gomez-Rodriguez, Jure Leskovec, Bernhard Schölkopf: Structure and dynamics of information pathways in online media. WSDM 2013: 23-32

David Lopez-Paz, José Miguel Hernández-Lobato, Bernhard Schölkopf: Semi-Supervised Domain Adaptation with Non-Parametric Copulas. CoRR abs/1301.0142 (2013)

Krikamol Muandet, David Balduzzi, Bernhard Schölkopf: Domain Generalization via Invariant Feature Representation. CoRR abs/1301.2115 (2013)

Krikamol Muandet, Bernhard Schölkopf: One-Class Support Measure Machines for Group Anomaly Detection. CoRR abs/1303.0309 (2013)

Joris M. Mooij, Dominik Janzing, Bernhard Schölkopf: From Ordinary Differential Equations to Structural Causal Models: the deterministic case. CoRR abs/1304.7920 (2013)

Dominik Janzing, Joris M. Mooij, Kun Zhang, Jan Lemeire, Jakob Zscheischler, Povilas Daniusis, Bastian Steudel, Bernhard Schölkopf: Information-geometric approach to inferring causal directions. Artif. Intell. 182-183: 1-31 (2012)

Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola: A Kernel Two-Sample Test. Journal of Machine Learning Research 13: 723-773 (2012)

Rolf Köhler, Michael Hirsch, Betty J. Mohler, Bernhard Schölkopf, Stefan Harmeling: Recording and Playback of Camera Shake: Benchmarking Blind Deconvolution with a Real-World Database. ECCV (7) 2012: 27-40

Christian J. Schuler, Michael Hirsch, Stefan Harmeling, Bernhard Schölkopf: Blind Correction of Optical Aberrations. ECCV (3) 2012: 187-200

Michael Hirsch, Matthias Hofmann, Frederic Mantlik, Bernd J. Pichler, Bernhard Schölkopf, Michael Habeck: A blind deconvolution approach for pseudo CT prediction from MR image pairs. ICIP 2012: 2953-2956

Manuel Gomez-Rodriguez, Bernhard Schölkopf: Influence Maximization in Continuous Time Diffusion Networks. ICML 2012

Manuel Gomez-Rodriguez, Bernhard Schölkopf: Submodular Inference of Diffusion Networks from Multiple Trees. ICML 2012

Bernhard Schölkopf, Dominik Janzing, Jonas Peters, Eleni Sgouritsa, Kun Zhang, Joris M. Mooij: On causal and anticausal learning. ICML 2012

Timm Meyer, Jan Peters, Doris Brtz, Thorsten O. Zander, Bernhard Schölkopf, Surjo R. Soekadar, Moritz Grosse-Wentrup: A brain-robot interface for studying motor learning after stroke. IROS 2012: 4078-4083

Krikamol Muandet, Kenji Fukumizu, Francesco Dinuzzo, Bernhard Schölkopf: Learning from Distributions via Support Measure Machines. NIPS 2012: 10-18

Francesco Dinuzzo, Bernhard Schölkopf: The representer theorem for Hilbert spaces: a necessary and sufficient condition. NIPS 2012: 189-196

David López-Paz, José Miguel Hernández-Lobato, Bernhard Schölkopf: Semi-Supervised Domain Adaptation with Non-Parametric Copulas. NIPS 2012: 674-682

Zhikun Wang, Marc Peter Deisenroth, Heni Ben Amor, David Vogt, Bernhard Schölkopf, Jan Peters: Probabilistic Modeling of Human Movements for Intention Inference. Robotics: Science and Systems 2012

Dominik Janzing, Eleni Sgouritsa, Oliver Stegle, Jonas Peters, Bernhard Schölkopf: Detecting low-complexity unobserved causes. CoRR abs/1202.3737 (2012)

Jonas Peters, Joris M. Mooij, Dominik Janzing, Bernhard Schölkopf: Identifiability of Causal Graphs using Functional Models. CoRR abs/1202.3757 (2012)

Kun Zhang, Jonas Peters, Dominik Janzing, Bernhard Schölkopf: Kernel-based Conditional Independence Test and Application in Causal Discovery. CoRR abs/1202.3775 (2012)

Krikamol Muandet, Bernhard Schölkopf, Kenji Fukumizu, Francesco Dinuzzo: Learning from Distributions via Support Measure Machines. CoRR abs/1202.6504 (2012)

Povilas Daniusis, Dominik Janzing, Joris M. Mooij, Jakob Zscheischler, Bastian Steudel, Kun Zhang, Bernhard Schölkopf: Inferring deterministic causal relations. CoRR abs/1203.3475 (2012)

Kun Zhang, Bernhard Schölkopf, Dominik Janzing: Invariant Gaussian Process Latent Variable Models and Application in Causal Discovery. CoRR abs/1203.3534 (2012)

Manuel Gomez-Rodriguez, Bernhard Schölkopf: Submodular Inference of Diffusion Networks from Multiple Trees. CoRR abs/1205.1671 (2012)

Manuel Gomez-Rodriguez, Bernhard Schölkopf: Influence Maximization in Continuous Time Diffusion Networks. CoRR abs/1205.1682 (2012)

Francesco Dinuzzo, Bernhard Schölkopf: The representer theorem for Hilbert spaces: a necessary and sufficient condition. CoRR abs/1205.1928 (2012)

Dominik Janzing, Jonas Peters, Joris M. Mooij, Bernhard Schölkopf: Identifying confounders using additive noise models. CoRR abs/1205.2640 (2012)

Jonas Peters, Dominik Janzing, Bernhard Schölkopf: Causal Inference on Time Series using Structural Equation Models. CoRR abs/1207.5136 (2012)

Manuel Gomez-Rodriguez, Jure Leskovec, Bernhard Schölkopf: Structure and Dynamics of Information Pathways in Online Media. CoRR abs/1212.1464 (2012)

Dominik Grimm, Bastian Greshake, Stefan Kleeberger, Christoph Lippert, Oliver Stegle, Bernhard Schölkopf, Detlef Weigel, Karsten M. Borgwardt: easyGWAS: An integrated interspecies platform for performing genome-wide association studies. CoRR abs/1212.4788 (2012)

Henry Horng-Shing Lu, Bernhard Schölkopf, Hongyu Zhao (Eds.): Handbook of Statistical Bioinformatics. Springer Handbooks of Computational Statistics, Springer 2011, isbn 978-3-642-16344-9

Michael Hirsch, Bernhard Schölkopf, Michael Habeck: A Blind Deconvolution Approach for Improving the Resolution of Cryo-EM Density Maps. Journal of Computational Biology 18(3): 335-346 (2011)

Elisabeth Georgii, Koji Tsuda, Bernhard Schölkopf: Multi-way set enumeration in weight tensors. Machine Learning 82(2): 123-155 (2011)

Suzanna Martens, Joris M. Mooij, N. Jeremy Hill, Jason Farquhar, Bernhard Schölkopf: A Graphical Model Framework for Decoding in the Visual ERP-Based BCI Speller. Neural Computation 23(1): 160-182 (2011)

Moritz Grosse-Wentrup, Bernhard Schölkopf, N. Jeremy Hill: Causal influence of gamma oscillations on the sensorimotor rhythm. NeuroImage 56(2): 837-842 (2011)

Jonas Peters, Dominik Janzing, Bernhard Schölkopf: Causal Inference on Discrete Data Using Additive Noise Models. IEEE Trans. Pattern Anal. Mach. Intell. 33(12): 2436-2450 (2011)

Michel Besserve, Dominik Janzing, Nikos K. Logothetis, Bernhard Schölkopf: Finding dependencies between frequencies with the kernel cross-spectral density. ICASSP 2011: 2080-2083

Michael Hirsch, Christian J. Schuler, Stefan Harmeling, Bernhard Schölkopf: Fast removal of non-uniform camera shake. ICCV 2011: 463-470

Christian J. Schuler, Michael Hirsch, Stefan Harmeling, Bernhard Schölkopf: Non-stationary correction of optical aberrations. ICCV 2011: 659-666

Manuel Gomez-Rodriguez, David Balduzzi, Bernhard Schölkopf: Uncovering the Temporal Dynamics of Diffusion Networks. ICML 2011: 561-568

Vojtech Franc, Alexander Zien, Bernhard Schölkopf: Support Vector Machines as Probabilistic Models. ICML 2011: 665-672

Zhikun Wang, Christoph H. Lampert, Katharina Mülling, Bernhard Schölkopf, Jan Peters: Learning anticipation policies for robot table tennis. IROS 2011: 332-337

Botond Bocsi, Duy Nguyen-Tuong, Lehel Csató, Bernhard Schölkopf, Jan Peters: Learning inverse kinematics with structured prediction. IROS 2011: 698-703

Panagiotis Achlioptas, Bernhard Schölkopf, Karsten M. Borgwardt: Two-locus association mapping in subquadratic time. KDD 2011: 726-734

Joris M. Mooij, Dominik Janzing, Tom Heskes, Bernhard Schölkopf: On Causal Discovery with Cyclic Additive Noise Models. NIPS 2011: 639-647

Peter V. Gehler, Carsten Rother, Martin Kiefel, Lumin Zhang, Bernhard Schölkopf: Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance. NIPS 2011: 765-773

Dominik Janzing, Eleni Sgouritsa, Oliver Stegle, Jonas Peters, Bernhard Schölkopf: Detecting low-complexity unobserved causes. UAI 2011: 383-391

Jonas Peters, Joris M. Mooij, Dominik Janzing, Bernhard Schölkopf: Identifiability of Causal Graphs using Functional Models. UAI 2011: 589-598

Kun Zhang, Jonas Peters, Dominik Janzing, Bernhard Schölkopf: Kernel-based Conditional Independence Test and Application in Causal Discovery. UAI 2011: 804-813

Manuel Gomez-Rodriguez, David Balduzzi, Bernhard Schölkopf: Uncovering the Temporal Dynamics of Diffusion Networks. CoRR abs/1105.0697 (2011)

Bernhard Schölkopf, Dominik Janzing, Jonas Peters, Kun Zhang: Robust Learning via Cause-Effect Models. CoRR abs/1112.2738 (2011)

Michel Besserve, Bernhard Schölkopf, Nikos K. Logothetis, Stefano Panzeri: Causal relationships between frequency bands of extracellular signals in visual cortex revealed by an information theoretic analysis. Journal of Computational Neuroscience 29(3): 547-566 (2010)

Isabelle Guyon, Dominik Janzing, Bernhard Schölkopf: Causality: Objectives and Assessment. Journal of Machine Learning Research - Proceedings Track 6: 1-42 (2010)

Jonas Peters, Dominik Janzing, Bernhard Schölkopf: Identifying Cause and Effect on Discrete Data using Additive Noise Models. Journal of Machine Learning Research - Proceedings Track 9: 597-604 (2010)

Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Bernhard Schölkopf, Gert R. G. Lanckriet: Hilbert Space Embeddings and Metrics on Probability Measures. Journal of Machine Learning Research 11: 1517-1561 (2010)

Florian Steinke, Matthias Hein, Bernhard Schölkopf: Nonparametric Regression between General Riemannian Manifolds. SIAM J. Imaging Sciences 3(3): 527-563 (2010)

Dominik Janzing, Bernhard Schölkopf: Causal inference using the algorithmic Markov condition. IEEE Transactions on Information Theory 56(10): 5168-5194 (2010)

Bastian Steudel, Dominik Janzing, Bernhard Schölkopf: Causal Markov Condition for Submodular Information Measures. COLT 2010: 464-476

Michael Hirsch, Suvrit Sra, Bernhard Schölkopf, Stefan Harmeling: Efficient filter flow for space-variant multiframe blind deconvolution. CVPR 2010: 607-614

Stefan Harmeling, Suvrit Sra, Michael Hirsch, Bernhard Schölkopf: Multiframe blind deconvolution, super-resolution, and saturation correction via incremental EM. ICIP 2010: 3313-3316

Dominik Janzing, Patrik O. Hoyer, Bernhard Schölkopf: Telling cause from effect based on high-dimensional observations. ICML 2010: 479-486

Jens Kober, Katharina Mülling, Oliver Kroemer, Christoph H. Lampert, Bernhard Schölkopf, Jan Peters: Movement templates for learning of hitting and batting. ICRA 2010: 853-858

Valentin Schwamberger, Pham Hai Dang Le, Bernhard Schölkopf, Matthias O. Franz: The Influence of the Image Basis on Modeling and Steganalysis Performance. Information Hiding 2010: 133-144

Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Bernhard Schölkopf, Gert R. G. Lanckriet: Non-parametric estimation of integral probability metrics. ISIT 2010: 1428-1432

Mauricio A. Álvarez, Jan Peters, Bernhard Schölkopf, Neil D. Lawrence: Switched Latent Force Models for Movement Segmentation. NIPS 2010: 55-63

Stefan Harmeling, Michael Hirsch, Bernhard Schölkopf: Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake. NIPS 2010: 829-837

Joris M. Mooij, Oliver Stegle, Dominik Janzing, Kun Zhang, Bernhard Schölkopf: Probabilistic latent variable models for distinguishing between cause and effect. NIPS 2010: 1687-1695

Michael Hirsch, Bernhard Schölkopf, Michael Habeck: A New Algorithm for Improving the Resolution of Cryo-EM Density Maps. RECOMB 2010: 174-188

Manuel Gomez-Rodriguez, Jan Peters, N. Jeremy Hill, Bernhard Schölkopf, Alireza Gharabaghi, Moritz Grosse-Wentrup: Closing the sensorimotor loop: Haptic feedback facilitates decoding of arm movement imagery. SMC 2010: 121-126

Povilas Daniusis, Dominik Janzing, Joris M. Mooij, Jakob Zscheischler, Bastian Steudel, Kun Zhang, Bernhard Schölkopf: Inferring deterministic causal relations. UAI 2010: 143-150

Kun Zhang, Bernhard Schölkopf, Dominik Janzing: Invariant Gaussian Process Latent Variable Models and Application in Causal Discovery. UAI 2010: 717-724

Bastian Steudel, Dominik Janzing, Bernhard Schölkopf: Causal Markov condition for submodular information measures. CoRR abs/1002.4020 (2010)

Hyunjung Shin, Koji Tsuda, Bernhard Schölkopf: Protein functional class prediction with a combined graph. Expert Syst. Appl. 36(2): 3284-3292 (2009)

Arnulf B. A. Graf, Olivier Bousquet, Gunnar Rätsch, Bernhard Schölkopf: Prototype Classification: Insights from Machine Learning. Neural Computation 21(1): 272-300 (2009)

Daewon Lee, Matthias Hofmann, Florian Steinke, Yasemin Altun, Nathan D. Cahill, Bernhard Schölkopf: Learning similarity measure for multi-modal 3D image registration. CVPR 2009: 186-193

Christian Walder, Martin Breidt, Heinrich H. Bülthoff, Bernhard Schölkopf, Cristóbal Curio: Markerless 3D Face Tracking. DAGM-Symposium 2009: 41-50

Joris M. Mooij, Dominik Janzing, Jonas Peters, Bernhard Schölkopf: Regression by dependence minimization and its application to causal inference in additive noise models. ICML 2009: 94

Jonas Peters, Dominik Janzing, Arthur Gretton, Bernhard Schölkopf: Detecting the direction of causal time series. ICML 2009: 101

Duy Nguyen-Tuong, Bernhard Schölkopf, Jan Peters: Sparse online model learning for robot control with support vector regression. IROS 2009: 3121-3126

Elisabeth Georgii, Koji Tsuda, Bernhard Schölkopf: Multi-way set enumeration in real-valued tensors. KDD Workshop on Data Mining using Matrices and Tensors 2009

Stefanie Jegelka, Arthur Gretton, Bernhard Schölkopf, Bharath K. Sriperumbudur, Ulrike von Luxburg: Generalized Clustering via Kernel Embeddings. KI 2009: 144-152

Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Gert R. G. Lanckriet, Bernhard Schölkopf: Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions. NIPS 2009: 1750-1758

Dominik Janzing, Jonas Peters, Joris M. Mooij, Bernhard Schölkopf: Identifying confounders using additive noise models. UAI 2009: 249-257

Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Gert R. G. Lanckriet, Bernhard Schölkopf: A note on integral probability metrics and $\phi$-divergences. CoRR abs/0901.2698 (2009)

Florian Steinke, Matthias Hein, Jan Peters, Bernhard Schölkopf: Manifold-valued Thin-Plate Splines with Applications in Computer Graphics. Comput. Graph. Forum 27(2): 437-448 (2008)

William T. Freeman, Pietro Perona, Bernhard Schölkopf: Guest Editorial. International Journal of Computer Vision 77(1-3): 1 (2008)

Xiaohai Sun, Dominik Janzing, Bernhard Schölkopf: Causal reasoning by evaluating the complexity of conditional densities with kernel methods. Neurocomputing 71(7-9): 1248-1256 (2008)

Asa Ben-Hur, Cheng Soon Ong, Sören Sonnenburg, Bernhard Schölkopf, Gunnar Rätsch: Support Vector Machines and Kernels for Computational Biology. PLoS Computational Biology 4(10) (2008)

Florian Steinke, Bernhard Schölkopf: Kernels, regularization and differential equations. Pattern Recognition 41(11): 3271-3286 (2008)

Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Gert R. G. Lanckriet, Bernhard Schölkopf: Injective Hilbert Space Embeddings of Probability Measures. COLT 2008: 111-122

Guillaume Charpiat, Matthias Hofmann, Bernhard Schölkopf: Automatic Image Colorization Via Multimodal Predictions. ECCV (3) 2008: 126-139

Duy Nguyen-Tuong, Jan Peters, Matthias Seeger, Bernhard Schölkopf: Learning Inverse Dynamics: a Comparison. ESANN 2008: 13-18

Pia Breuer, Kwang In Kim, Wolf Kienzle, Bernhard Schölkopf, Volker Blanz: Automatic 3D face reconstruction from single images or video. FG 2008: 1-8

Jonas Peters, Dominik Janzing, Arthur Gretton, Bernhard Schölkopf: Kernel Methods for Detecting the Direction of Time Series. GfKl 2008: 57-66

Le Song, Xinhua Zhang, Alex J. Smola, Arthur Gretton, Bernhard Schölkopf: Tailoring density estimation via reproducing kernel moment matching. ICML 2008: 992-999

Christian Walder, Kwang In Kim, Bernhard Schölkopf: Sparse multiscale gaussian process regression. ICML 2008: 1112-1119

Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf: Characteristic Kernels on Groups and Semigroups. NIPS 2008: 473-480

N. Jeremy Hill, Jason Farquhar, Suzanna Martens, Felix Bießmann, Bernhard Schölkopf: Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance. NIPS 2008: 665-672

Patrik O. Hoyer, Dominik Janzing, Joris M. Mooij, Jonas Peters, Bernhard Schölkopf: Nonlinear causal discovery with additive noise models. NIPS 2008: 689-696

Gabriele Schweikert, Christian Widmer, Bernhard Schölkopf, Gunnar Rätsch: An Empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence Analysis. NIPS 2008: 1433-1440

Matthias W. Seeger, Hannes Nickisch, Rolf Pohmann, Bernhard Schölkopf: Bayesian Experimental Design of Magnetic Resonance Imaging Sequences. NIPS 2008: 1441-1448

Christian Walder, Bernhard Schölkopf: Diffeomorphic Dimensionality Reduction. NIPS 2008: 1713-1720

Dominik Janzing, Bernhard Schölkopf: Causal inference using the algorithmic Markov condition. CoRR abs/0804.3678 (2008)

Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola: A Kernel Method for the Two-Sample Problem. CoRR abs/0805.2368 (2008)

Mingrui Wu, Bernhard Schölkopf: Transductive Classification via Local Learning Regularization. Journal of Machine Learning Research - Proceedings Track 2: 628-635 (2007)

Sören Sonnenburg, Mikio L. Braun, Cheng Soon Ong, Samy Bengio, Léon Bottou, Geoffrey Holmes, Yann LeCun, Klaus-Robert Müller, Fernando Pereira, Carl Edward Rasmussen, Gunnar Rätsch, Bernhard Schölkopf, Alexander J. Smola, Pascal Vincent, Jason Weston, Robert C. Williamson: The Need for Open Source Software in Machine Learning. Journal of Machine Learning Research 8: 2443-2466 (2007)

Gunnar Rätsch, Sören Sonnenburg, Jagan Srinivasan, Hanh Witte, Klaus-Robert Müller, Ralf J. Sommer, Bernhard Schölkopf: Improving the Caenorhabditis elegans Genome Annotation Using Machine Learning. PLoS Computational Biology 3(2) (2007)

Tobias Pfingsten, Daniel J. L. Herrmann, Thomas Schnitzler, Andreas Feustel, Bernhard Schölkopf: Feature Selection for Troubleshooting in Complex Assembly Lines. IEEE T. Automation Science and Engineering 4(3): 465-469 (2007)

Stephan Waldert, Michael Bensch, Martin Bogdan, Wolfgang Rosenstiel, Bernhard Schölkopf, Curtis L. Lowery, Hari Eswaran, Hubert Preissl: Real-Time Fetal Heart Monitoring in Biomagnetic Measurements Using Adaptive Real-Time ICA. IEEE Trans. Biomed. Engineering 54(10): 1867-1874 (2007)

Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola: A Kernel Approach to Comparing Distributions. AAAI 2007: 1637-1641

Alex J. Smola, Arthur Gretton, Le Song, Bernhard Schölkopf: A Hilbert Space Embedding for Distributions. ALT 2007: 13-31

Jan Peters, Stefan Schaal, Bernhard Schölkopf: Towards Machine Learning of Motor Skills. AMS 2007: 138-144

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. DAGM-Symposium 2007: 405-414

Alexander J. Smola, Arthur Gretton, Le Song, Bernhard Schölkopf: A Hilbert Space Embedding for Distributions. Discovery Science 2007: 40-41

Xiaohai Sun, Dominik Janzing, Bernhard Schölkopf: Distinguishing between cause and effect via kernel-based complexity measures for conditional distributions. ESANN 2007: 441-446

Xiaohai Sun, Dominik Janzing, Bernhard Schölkopf, Kenji Fukumizu: A kernel-based causal learning algorithm. ICML 2007: 855-862

Mingrui Wu, Kai Yu, Shipeng Yu, Bernhard Schölkopf: Local learning projections. ICML 2007: 1039-1046

Kenji Fukumizu, Arthur Gretton, Xiaohai Sun, Bernhard Schölkopf: Kernel Measures of Conditional Dependence. NIPS 2007

Arthur Gretton, Kenji Fukumizu, Choon Hui Teo, Le Song, Bernhard Schölkopf, Alex J. Smola: A Kernel Statistical Test of Independence. NIPS 2007

Fabian H. Sinz, Olivier Chapelle, Alekh Agarwal, Bernhard Schölkopf: An Analysis of Inference with the Universum. NIPS 2007

Bernhard Schölkopf, John C. Platt, Thomas Hoffman (Eds.): Advances in Neural Information Processing Systems 19, Proceedings of the Twentieth Annual Conference on Neural Information Processing Systems, Vancouver, British Columbia, Canada, December 4-7, 2006. MIT Press 2007, isbn 0-262-19568-2

Christian Walder, Bernhard Schölkopf, Olivier Chapelle: Implicit Surface Modelling with a Globally Regularised Basis of Compact Support. Comput. Graph. Forum 25(3): 635-644 (2006)

Mingrui Wu, Bernhard Schölkopf, Gökhan H. Bakir: A Direct Method for Building Sparse Kernel Learning Algorithms. Journal of Machine Learning Research 7: 603-624 (2006)

Sören Sonnenburg, Gunnar Rätsch, Christin Schäfer, Bernhard Schölkopf: Large Scale Multiple Kernel Learning. Journal of Machine Learning Research 7: 1531-1565 (2006)

Arnulf B. A. Graf, Felix A. Wichmann, Heinrich H. Bülthoff, Bernhard Schölkopf: Classification of Faces in Man and Machine. Neural Computation 18(1): 143-165 (2006)

Matthias O. Franz, Bernhard Schölkopf: A Unifying View of Wiener and Volterra Theory and Polynomial Kernel Regression. Neural Computation 18(12): 3097-3118 (2006)

N. Jeremy Hill, Thomas Navin Lal, Michael Schröder, Thilo Hinterberger, Guido Widman, Christian Erich Elger, Bernhard Schölkopf, Niels Birbaumer: Classifying Event-Related Desynchronization in EEG, ECoG and MEG Signals. DAGM-Symposium 2006: 404-413

Xiaohai Sun, Dominik Janzing, Bernhard Schölkopf: Causal Inference by Choosing Graphs with Most Plausible Markov Kernels. ISAIM 2006

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. ISMB (Supplement of Bioinformatics) 2006: 49-57

Christian Walder, Bernhard Schölkopf, Olivier Chapelle: Implicit Surfaces with Globally Regularised and Compactly Supported Basis Functions. NIPS 2006: 273-280

Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola: A Kernel Method for the Two-Sample-Problem. NIPS 2006: 513-520

Jiayuan Huang, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt, Bernhard Schölkopf: Correcting Sample Selection Bias by Unlabeled Data. NIPS 2006: 601-608

Wolf Kienzle, Felix A. Wichmann, Bernhard Schölkopf, Matthias O. Franz: A Nonparametric Approach to Bottom-Up Visual Saliency. NIPS 2006: 689-696

Florian Steinke, Bernhard Schölkopf, Volker Blanz: Learning Dense 3D Correspondence. NIPS 2006: 1313-1320

Mingrui Wu, Bernhard Schölkopf: A Local Learning Approach for Clustering. NIPS 2006: 1529-1536

Dengyong Zhou, Jiayuan Huang, Bernhard Schölkopf: Learning with Hypergraphs: Clustering, Classification, and Embedding. NIPS 2006: 1601-1608

Florian Steinke, Bernhard Schölkopf, Volker Blanz: Support Vector Machines for 3D Shape Processing. Comput. Graph. Forum 24(3): 285-294 (2005)

Michael Schröder, Thomas Navin Lal, Thilo Hinterberger, Martin Bogdan, N. Jeremy Hill, Niels Birbaumer, Wolfgang Rosenstiel, Bernhard Schölkopf: Robust EEG Channel Selection across Subjects for Brain-Computer Interfaces. EURASIP J. Adv. Sig. Proc. 2005(19): 3103-3112 (2005)

Matthias Hein, Olivier Bousquet, Bernhard Schölkopf: Maximal margin classification for metric spaces. J. Comput. Syst. Sci. 71(3): 333-359 (2005)

Arthur Gretton, Ralf Herbrich, Alexander J. Smola, Olivier Bousquet, Bernhard Schölkopf: Kernel Methods for Measuring Independence. Journal of Machine Learning Research 6: 2075-2129 (2005)

Athanassia Chalimourda, Bernhard Schölkopf, Alex J. Smola: Experimentally optimal nu in support vector regression for different noise models and parameter settings. Neural Networks 18(2): 205- (2005)

Kwang In Kim, Matthias O. Franz, Bernhard Schölkopf: Iterative Kernel Principal Component Analysis for Image Modeling. IEEE Trans. Pattern Anal. Mach. Intell. 27(9): 1351-1366 (2005)

Arthur Gretton, Olivier Bousquet, Alex J. Smola, Bernhard Schölkopf: Measuring Statistical Dependence with Hilbert-Schmidt Norms. ALT 2005: 63-77

Dengyong Zhou, Bernhard Schölkopf: Regularization on Discrete Spaces. DAGM-Symposium 2005: 361-368

Koji Tsuda, Hyunjung Shin, Bernhard Schölkopf: Fast protein classification with multiple networks. ECCB/JBI 2005: 65

Wolf Kienzle, Bernhard Schölkopf: Training Support Vector Machines with Multiple Equality Constraints. ECML 2005: 182-193

Thomas Navin Lal, Michael Schröder, 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. ICML 2005: 465-472

Bernhard Schölkopf, Florian Steinke, Volker Blanz: Object correspondence as a machine learning problem. ICML 2005: 776-783

Sören Sonnenburg, Gunnar Rätsch, Bernhard Schölkopf: Large scale genomic sequence SVM classifiers. ICML 2005: 848-855

Christian Walder, Olivier Chapelle, Bernhard Schölkopf: Implicit surface modelling as an eigenvalue problem. ICML 2005: 936-939

Mingrui Wu, Bernhard Schölkopf, Gökhan H. Bakir: Building Sparse Large Margin Classifiers. ICML 2005: 996-1003

Dengyong Zhou, Jiayuan Huang, Bernhard Schölkopf: Learning from labeled and unlabeled data on a directed graph. ICML 2005: 1036-1043

Gunnar Rätsch, Sören Sonnenburg, Bernhard Schölkopf: RASE: recognition of alternatively spliced exons in C.elegans. ISMB (Supplement of Bioinformatics) 2005: 369-377

Jason Weston, Bernhard Schölkopf, Olivier Bousquet: Joint Kernel Maps. IWANN 2005: 176-191

Tobias Jung, Luis Herrera, Bernhard Schölkopf: Long Term Prediction of Product Quality in a Glass Manufacturing Process Using a Kernel Based Approach. IWANN 2005: 960-967

Joaquin Quiñonero Candela, Carl Edward Rasmussen, Fabian H. Sinz, Olivier Bousquet, Bernhard Schölkopf: Evaluating Predictive Uncertainty Challenge. MLCW 2005: 1-27

Holger Fröhlich, Olivier Chapelle, Bernhard Schölkopf: Feature Selection for Support Vector Machines Using Genetic Algorithms. International Journal on Artificial Intelligence Tools 13(4): 791-800 (2004)

Ulrike von Luxburg, Olivier Bousquet, Bernhard Schölkopf: A Compression Approach to Support Vector Model Selection. Journal of Machine Learning Research 5: 293-323 (2004)

Athanassia Chalimourda, Bernhard Schölkopf, Alex J. Smola: Experimentally optimal v in support vector regression for different noise models and parameter settings. Neural Networks 17(1): 127-141 (2004)

Alexander J. Smola, Bernhard Schölkopf: A tutorial on support vector regression. Statistics and Computing 14(3): 199-222 (2004)

Thomas Navin Lal, Michael Schröder, Thilo Hinterberger, Jason Weston, Martin Bogdan, Niels Birbaumer, Bernhard Schölkopf: Support vector channel selection in BCI. IEEE Trans. Biomed. Engineering 51(6): 1003-1010 (2004)

Matthias O. Franz, Younghee Kwon, Carl Edward Rasmussen, Bernhard Schölkopf: Semi-supervised Kernel Regression Using Whitened Function Classes. DAGM-Symposium 2004: 18-26

Wolf Kienzle, Gökhan H. Bakir, Matthias O. Franz, Bernhard Schölkopf: Efficient Approximations for Support Vector Machines in Object Detection. DAGM-Symposium 2004: 54-61

Dengyong Zhou, Bernhard Schölkopf: Learning from Labeled and Unlabeled Data Using Random Walks. DAGM-Symposium 2004: 237-244

Gökhan H. Bakir, Arthur Gretton, Matthias O. Franz, Bernhard Schölkopf: Multivariate Regression via Stiefel Manifold Constraints. DAGM-Symposium 2004: 262-269

Jihun Ham, Daniel D. Lee, Sebastian Mika, Bernhard Schölkopf: A kernel view of the dimensionality reduction of manifolds. ICML 2004

Matthias O. Franz, Bernhard Schölkopf: Implicit Wiener Series for Higher-Order Image Analysis. NIPS 2004

N. Jeremy Hill, Thomas Navin Lal, Karin Bierig, Niels Birbaumer, Bernhard Schölkopf: An Auditory Paradigm for Brain-Computer Interfaces. NIPS 2004

Wolf Kienzle, Gökhan H. Bakir, Matthias O. Franz, Bernhard Schölkopf: Face Detection - Efficient and Rank Deficient. NIPS 2004

Thomas Navin Lal, Thilo Hinterberger, Guido Widman, Michael Schröder, N. Jeremy Hill, Wolfgang Rosenstiel, Christian Erich Elger, Bernhard Schölkopf, Niels Birbaumer: Methods Towards Invasive Human Brain Computer Interfaces. NIPS 2004

Bernhard Schölkopf, Joachim Giesen, Simon Spalinger: Kernel Methods for Implicit Surface Modeling. NIPS 2004

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. NIPS 2004

Dengyong Zhou, Bernhard Schölkopf, Thomas Hofmann: Semi-supervised Learning on Directed Graphs. NIPS 2004

Carl Edward Rasmussen, Heinrich H. Bülthoff, Bernhard Schölkopf, Martin A. Giese (Eds.): Pattern Recognition, 26th DAGM Symposium, August 30 - September 1, 2004, Tübingen, Germany, Proceedings. Lecture Notes in Computer Science 3175, Springer 2004, isbn 3-540-22945-0

Sebastian Thrun, Lawrence K. Saul, Bernhard Schölkopf (Eds.): Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, NIPS 2003, December 8-13, 2003, Vancouver and Whistler, British Columbia, Canada]. MIT Press 2004, isbn 0-262-20152-6

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. Bioinformatics 19(6): 764-771 (2003)

Bernhard Schölkopf: Statistical learning theory, capacity, and complexity. Complexity 8(4): 87-94 (2003)

Jason Weston, André Elisseeff, Bernhard Schölkopf, Michael E. Tipping: Use of the Zero-Norm with Linear Models and Kernel Methods. Journal of Machine Learning Research 3: 1439-1461 (2003)

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. IEEE Trans. Pattern Anal. Mach. Intell. 25(5): 623-633 (2003)

Holger Fröhlich, Olivier Chapelle, Bernhard Schölkopf: Feature Selection for Support Vector Machines by Means of Genetic Algorithms. ICTAI 2003: 142-148

Gökhan H. Bakir, Jason Weston, Bernhard Schölkopf: Learning to Find Pre-Images. NIPS 2003

Jan Eichhorn, Andreas S. Tolias, Alexander Zien, Malte Kuss, Carl Edward Rasmussen, Jason Weston, Nikos K. Logothetis, Bernhard Schölkopf: Prediction on Spike Data Using Kernel Algorithms. NIPS 2003

Dengyong Zhou, Olivier Bousquet, Thomas Navin Lal, Jason Weston, Bernhard Schölkopf: Learning with Local and Global Consistency. NIPS 2003

Dengyong Zhou, Jason Weston, Arthur Gretton, Olivier Bousquet, Bernhard Schölkopf: Ranking on Data Manifolds. NIPS 2003

Bernhard Schölkopf, Manfred K. Warmuth (Eds.): Computational Learning Theory and Kernel Machines, 16th Annual Conference on Computational Learning Theory and 7th Kernel Workshop, COLT/Kernel 2003, Washington, DC, USA, August 24-27, 2003, Proceedings. Lecture Notes in Computer Science 2777, Springer 2003, isbn 3-540-40720-0

Nello Cristianini, Bernhard Schölkopf: Support Vector Machines and Kernel Methods: The New Generation of Learning Machines. AI Magazine 23(3): 31-42 (2002)

Dennis DeCoste, Bernhard Schölkopf: Training Invariant Support Vector Machines. Machine Learning 46(1-3): 161-190 (2002)

Gunnar Rätsch, Sebastian Mika, Bernhard Schölkopf, Klaus-Robert Müller: Constructing Boosting Algorithms from SVMs: An Application to One-Class Classification. IEEE Trans. Pattern Anal. Mach. Intell. 24(9): 1184-1199 (2002)

Bernhard Schölkopf, Jason Weston, Eleazar Eskin, Christina S. Leslie, William Stafford Noble: A Kernel Approach for Learning from almost Orthogonal Patterns. ECML 2002: 511-528

Bernhard Schölkopf, Alex J. Smola: A Short Introduction to Learning with Kernels. Machine Learning Summer School 2002: 41-64

Alex J. Smola, Bernhard Schölkopf: Bayesian Kernel Methods. Machine Learning Summer School 2002: 65-117

Olivier Chapelle, Jason Weston, Bernhard Schölkopf: Cluster Kernels for Semi-Supervised Learning. NIPS 2002: 585-592

Jason Weston, Olivier Chapelle, André Elisseeff, Bernhard Schölkopf, Vladimir Vapnik: Kernel Dependency Estimation. NIPS 2002: 873-880

Bernhard Schölkopf, Jason Weston, Eleazar Eskin, Christina S. Leslie, William Stafford Noble: A Kernel Approach for Learning from Almost Orthogonal Patterns. PKDD 2002: 494-511

Alex J. Smola, Sebastian Mika, Bernhard Schölkopf, Robert C. Williamson: Regularized Principal Manifolds. Journal of Machine Learning Research 1: 179-209 (2001)

Bernhard Schölkopf, John C. Platt, John Shawe-Taylor, Alex J. Smola, Robert C. Williamson: Estimating the Support of a High-Dimensional Distribution. Neural Computation 13(7): 1443-1471 (2001)

Robert C. Williamson, Alex J. Smola, Bernhard Schölkopf: Generalization performance of regularization networks and support vector machines via entropy numbers of compact operators. IEEE Transactions on Information Theory 47(6): 2516-2532 (2001)

Klaus-Robert Müller, Sebastian Mika, Gunnar Rätsch, Koji Tsuda, Bernhard Schölkopf: An introduction to kernel-based learning algorithms. IEEE Transactions on Neural Networks 12(2): 181-201 (2001)

Bernhard Schölkopf, Ralf Herbrich, Alex J. Smola: A Generalized Representer Theorem. COLT/EuroCOLT 2001: 416-426

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. ICCV 2001: 674-679

Sami Romdhani, Philip H. S. Torr, Bernhard Schölkopf, Andrew Blake: Computationally Efficient Face Detection. ICCV 2001: 695-700

Neil D. Lawrence, Bernhard Schölkopf: Estimating a Kernel Fisher Discriminant in the Presence of Label Noise. ICML 2001: 306-313

Dimitris Achlioptas, Frank McSherry, Bernhard Schölkopf: Sampling Techniques for Kernel Methods. NIPS 2001: 335-342

Olivier Chapelle, Bernhard Schölkopf: Incorporating Invariances in Non-Linear Support Vector Machines. NIPS 2001: 609-616

Alexander Zien, Gunnar Rätsch, Sebastian Mika, Bernhard Schölkopf, Thomas Lengauer, Klaus-Robert Müller: Engineering support vector machine kernels that recognize translation initiation sites. Bioinformatics 16(9): 799-807 (2000)

Bernhard Schölkopf, Alex J. Smola, Robert C. Williamson, Peter L. Bartlett: New Support Vector Algorithms. Neural Computation 12(5): 1207-1245 (2000)

Robert C. Williamson, Alex J. Smola, Bernhard Schölkopf: Entropy Numbers of Linear Function Classes. COLT 2000: 309-319

Alex J. Smola, Bernhard Schölkopf: Sparse Greedy Matrix Approximation for Machine Learning. ICML 2000: 911-918

Athanassia Chalimourda, Bernhard Schölkopf, Alex J. Smola: Choosing in Support Vector Regression with Different Noise Models: Theory and Experiments. IJCNN (5) 2000: 199-204

Bernhard Schölkopf: The Kernel Trick for Distances. NIPS 2000: 301-307

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. NIPS 2000: 741-747

Paul M. Hayton, Bernhard Schölkopf, Lionel Tarassenko, Paul Anuzis: Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra. NIPS 2000: 946-952

Gunnar Rätsch, Bernhard Schölkopf, Alex J. Smola, Sebastian Mika, Takashi Onoda, Klaus-Robert Müller: Robust Ensemble Learning for Data Mining. PAKDD 2000: 341-344

Bernhard Schölkopf, Klaus-Robert Müller, Alex J. Smola: Lernen mit Kernen: Support-Vektor-Methoden zur Analyse hochdimensionaler Daten. Inform., Forsch. Entwickl. 14(3): 154-163 (1999)

Bernhard Schölkopf, Sebastian Mika, Christopher J. C. Burges, Phil Knirsch, Klaus-Robert Müller, Gunnar Rätsch, Alexander J. Smola: Input space versus feature space in kernel-based methods. IEEE Transactions on Neural Networks 10(5): 1000-1017 (1999)

Alex J. Smola, Robert C. Williamson, Sebastian Mika, Bernhard Schölkopf: Regularized Principal Manifolds. EuroCOLT 1999: 214-229

Robert C. Williamson, Alex J. Smola, Bernhard Schölkopf: Entropy Numbers, Operators and Support Vector Kernels. EuroCOLT 1999: 285-299

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. German Conference on Bioinformatics 1999: 37-43

Alex J. Smola, John Shawe-Taylor, Bernhard Schölkopf, Robert C. Williamson: The Entropy Regularization Information Criterion. NIPS 1999: 342-348

Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller: Invariant Feature Extraction and Classification in Kernel Spaces. NIPS 1999: 526-532

Gunnar Rätsch, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller, Takashi Onoda, Sebastian Mika: v-Arc: Ensemble Learning in the Presence of Outliers. NIPS 1999: 561-567

Bernhard Schölkopf, Robert C. Williamson, Alex J. Smola, John Shawe-Taylor, John C. Platt: Support Vector Method for Novelty Detection. NIPS 1999: 582-588

Alex J. Smola, Bernhard Schölkopf: On a Kernel-Based Method for Pattern Recognition, Regression, Approximation, and Operator Inversion. Algorithmica 22(1/2): 211-231 (1998)

Matthias O. Franz, Bernhard Schölkopf, Hanspeter A. Mallot, Heinrich H. Bülthoff: Learning View Graphs for Robot Navigation. Auton. Robots 5(1): 111-125 (1998)

Matthias O. Franz, Bernhard Schölkopf, Hanspeter A. Mallot, Heinrich H. Bülthoff: Where did I take that snapshot? Scene-based homing by image matching. Biological Cybernetics 79(3): 191-202 (1998)

Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller: Nonlinear Component Analysis as a Kernel Eigenvalue Problem. Neural Computation 10(5): 1299-1319 (1998)

Alex J. Smola, Bernhard Schölkopf, Klaus-Robert Müller: The connection between regularization operators and support vector kernels. Neural Networks 11(4): 637-649 (1998)

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. DAGM-Symposium 1998: 125-132

Matthias O. Franz, Bernhard Schölkopf, Hanspeter A. Mallot, Heinrich H. Bülthoff, Andreas Zell: Navigation mit Schnappschüssen. DAGM-Symposium 1998: 421-428

Bernhard Schölkopf, Peter L. Bartlett, Alex J. Smola, Robert C. Williamson: Shrinking the Tube: A New Support Vector Regression Algorithm. NIPS 1998: 330-336

Sebastian Mika, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller, Matthias Scholz, Gunnar Rätsch: Kernel PCA and De-Noising in Feature Spaces. NIPS 1998: 536-542

Alex J. Smola, Thilo-Thomas Frieß, Bernhard Schölkopf: Semiparametric Support Vector and Linear Programming Machines. NIPS 1998: 585-591

Bernhard Schölkopf, Kah Kay Sung, Christopher J. C. Burges, Federico Girosi, Partha Niyogi, Tomaso Poggio, Vladimir Vapnik: Comparing support vector machines with Gaussian kernels to radial basis function classifiers. IEEE Transactions on Signal Processing 45(11): 2758-2765 (1997)

Matthias O. Franz, Bernhard Schölkopf, Philip Georg, Hanspeter A. Mallot, Heinrich H. Bülthoff: Learning View Graphs for Robot Navigation. Agents 1997: 138-147

Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller: Kernel Principal Component Analysis. ICANN 1997: 583-588

Hanspeter A. Mallot, Matthias O. Franz, Bernhard Schölkopf, Heinrich H. Bülthoff: The View-Graph Approach to Visual Navigation and Spatial Memory. ICANN 1997: 751-756

Klaus-Robert Müller, Alex J. Smola, Gunnar Rätsch, Bernhard Schölkopf, Jens Kohlmorgen, Vladimir Vapnik: Predicting Time Series with Support Vector Machines. ICANN 1997: 999-1004

Bernhard Schölkopf, Patrice Simard, Alex J. Smola, Vladimir Vapnik: Prior Knowledge in Support Vector Kernels. NIPS 1997

Alex J. Smola, Bernhard Schölkopf: From Regularization Operators to Support Vector Kernels. NIPS 1997

Bernhard Schölkopf, Chris Burges, Vladimir Vapnik: Incorporating Invariances in Support Vector Learning Machines. ICANN 1996: 47-52

Volker Blanz, Bernhard Schölkopf, Heinrich H. Bülthoff, Chris Burges, Vladimir Vapnik, Thomas Vetter: Comparison of View-Based Object Recognition Algorithms Using Realistic 3D Models. ICANN 1996: 251-256

Christopher J. C. Burges, Bernhard Schölkopf: Improving the Accuracy and Speed of Support Vector Machines. NIPS 1996: 375-381

Bernhard Schölkopf, Chris Burges, Vladimir Vapnik: Extracting Support Data for a Given Task. KDD 1995: 252-257