Bernhard Schölkopf

According to our database1, Bernhard Schölkopf authored at least 357 papers between 1995 and 2019.

Collaborative distances:

Awards

ACM Fellow

ACM Fellow 2017, "For contributions to the theory and practice of machine learning".

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

Homepages:

On csauthors.net:

Bibliography

2019
Analysis of cause-effect inference by comparing regression errors.
PeerJ Computer Science, 2019

2018
Discriminative Transfer Learning for General Image Restoration.
IEEE Trans. Image Processing, 2018

Control of Musculoskeletal Systems Using Learned Dynamics Models.
IEEE Robotics and Automation Letters, 2018

Kernel Distribution Embeddings: Universal Kernels, Characteristic Kernels and Kernel Metrics on Distributions.
Journal of Machine Learning Research, 2018

Invariant Models for Causal Transfer Learning.
Journal of Machine Learning Research, 2018

Leveraging the Crowd to Detect and Reduce the Spread of Fake News and Misinformation.
Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, 2018

From Deterministic ODEs to Dynamic Structural Causal Models.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Adaptive Skip Intervals: Temporal Abstraction for Recurrent Dynamical Models.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Informative Features for Model Comparison.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Generalized Score Functions for Causal Discovery.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Tempered Adversarial Networks.
Proceedings of the 35th International Conference on Machine Learning, 2018

Learning Independent Causal Mechanisms.
Proceedings of the 35th International Conference on Machine Learning, 2018

On Matching Pursuit and Coordinate Descent.
Proceedings of the 35th International Conference on Machine Learning, 2018

Detecting non-causal artifacts in multivariate linear regression models.
Proceedings of the 35th International Conference on Machine Learning, 2018

Differentially Private Database Release via Kernel Mean Embeddings.
Proceedings of the 35th International Conference on Machine Learning, 2018

Wasserstein Auto-Encoders.
Proceedings of the 6th International Conference on Learning Representations, 2018

Tempered Adversarial Networks.
Proceedings of the 6th International Conference on Learning Representations, 2018

Wasserstein Auto-Encoders: Latent Dimensionality and Random Encoders.
Proceedings of the 6th International Conference on Learning Representations, 2018

Learning Disentangled Representations with Wasserstein Auto-Encoders.
Proceedings of the 6th International Conference on Learning Representations, 2018

Clustering Meets Implicit Generative Models.
Proceedings of the 6th International Conference on Learning Representations, 2018

Fidelity-Weighted Learning.
Proceedings of the 6th International Conference on Learning Representations, 2018

Automatic estimation of modulation transfer functions.
Proceedings of the 2018 IEEE International Conference on Computational Photography, 2018

Spatio-Temporal Transformer Network for Video Restoration.
Proceedings of the Computer Vision - ECCV 2018, 2018

The Unreasonable Effectiveness of Texture Transfer for Single Image Super-Resolution.
Proceedings of the Computer Vision - ECCV 2018 Workshops, 2018

Efficient Encoding of Dynamical Systems Through Local Approximations.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Cause-Effect Inference by Comparing Regression Errors.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Group invariance principles for causal generative models.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
BundleMAP: Anatomically localized classification, regression, and hypothesis testing in diffusion MRI.
Pattern Recognition, 2017

Kernel Mean Embedding of Distributions: A Review and Beyond.
Foundations and Trends in Machine Learning, 2017

Anticipatory action selection for human-robot table tennis.
Artif. Intell., 2017

Distilling Information Reliability and Source Trustworthiness from Digital Traces.
Proceedings of the 26th International Conference on World Wide Web, 2017

DiSMEC: Distributed Sparse Machines for Extreme Multi-label Classification.
Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 2017

Causal Consistency of Structural Equation Models.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Causal Discovery from Temporally Aggregated Time Series.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Personalized brain-computer interface models for motor rehabilitation.
Proceedings of the 2017 IEEE International Conference on Systems, Man, and Cybernetics, 2017

AdaGAN: Boosting Generative Models.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Avoiding Discrimination through Causal Reasoning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Causal Discovery from Nonstationary/Heterogeneous Data: Skeleton Estimation and Orientation Determination.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Behind Distribution Shift: Mining Driving Forces of Changes and Causal Arrows.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Learning Blind Motion Deblurring.
Proceedings of the IEEE International Conference on Computer Vision, 2017

EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis.
Proceedings of the IEEE International Conference on Computer Vision, 2017

Online Video Deblurring via Dynamic Temporal Blending Network.
Proceedings of the IEEE International Conference on Computer Vision, 2017

A Guided Task for Cognitive brain-Computer Interfaces.
Proceedings of the From Vision to Reality, 2017

Closing One's eyes Affects amplitude modulation but not frequency modulation in a Cognitive BCI.
Proceedings of the From Vision to Reality, 2017

Flexible Spatio-Temporal Networks for Video Prediction.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Discovering Causal Signals in Images.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Local Group Invariant Representations via Orbit Embeddings.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Influence Estimation and Maximization in Continuous-Time Diffusion Networks.
ACM Trans. Inf. Syst., 2016

On Estimation of Functional Causal Models: General Results and Application to the Post-Nonlinear Causal Model.
ACM TIST, 2016

Preface to the ACM TIST Special Issue on Causal Discovery and Inference.
ACM TIST, 2016

Gaussian Process-Based Predictive Control for Periodic Error Correction.
IEEE Trans. Contr. Sys. Techn., 2016

Learning to Deblur.
IEEE Trans. Pattern Anal. Mach. Intell., 2016

Identification of causal relations in neuroimaging data with latent confounders: An instrumental variable approach.
NeuroImage, 2016

Kernel Mean Shrinkage Estimators.
Journal of Machine Learning Research, 2016

Distinguishing Cause from Effect Using Observational Data: Methods and Benchmarks.
Journal of Machine Learning Research, 2016

Estimating Diffusion Networks: Recovery Conditions, Sample Complexity and Soft-thresholding Algorithm.
Journal of Machine Learning Research, 2016

New Directions for Learning with Kernels and Gaussian Processes (Dagstuhl Seminar 16481).
Dagstuhl Reports, 2016

Unifying distillation and privileged information.
Proceedings of the 4th International Conference on Learning Representations, 2016

Transfer Learning in Brain-Computer Interfaces Abstract\uFFFDThe performance of brain-computer interfaces (BCIs) improves with the amount of avail.
IEEE Comp. Int. Mag., 2016

On the Identifiability and Estimation of Functional Causal Models in the Presence of Outcome-Dependent Selection.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

TerseSVM : A Scalable Approach for Learning Compact Models in Large-scale Classification.
Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Recovery of non-linear cause-effect relationships from linearly mixed neuroimaging data.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2016

Minimax Estimation of Maximum Mean Discrepancy with Radial Kernels.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Consistent Kernel Mean Estimation for Functions of Random Variables.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Domain Adaptation with Conditional Transferable Components.
Proceedings of the 33nd International Conference on Machine Learning, 2016

The Arrow of Time in Multivariate Time Series.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Jointly learning trajectory generation and hitting point prediction in robot table tennis.
Proceedings of the 16th IEEE-RAS International Conference on Humanoid Robots, 2016

Using probabilistic movement primitives for striking movements.
Proceedings of the 16th IEEE-RAS International Conference on Humanoid Robots, 2016

Approximate dual control maintaining the value of information with an application to building control.
Proceedings of the 2016 European Control Conference, 2016

Depth Estimation Through a Generative Model of Light Field Synthesis.
Proceedings of the Pattern Recognition - 38th German Conference, 2016

End-to-End Learning for Image Burst Deblurring.
Proceedings of the Computer Vision - ACCV 2016, 2016

2015
Computing functions of random variables via reproducing kernel Hilbert space representations.
Statistics and Computing, 2015

Causal interpretation rules for encoding and decoding models in neuroimaging.
NeuroImage, 2015

Artificial intelligence: Learning to see and act.
Nature, 2015

Semi-supervised interpolation in an anticausal learning scenario.
Journal of Machine Learning Research, 2015

A Cognitive Brain-Computer Interface for Patients with Amyotrophic Lateral Sclerosis.
Proceedings of the 2015 IEEE International Conference on Systems, 2015

BundleMAP: Anatomically Localized Features from dMRI for Detection of Disease.
Proceedings of the Machine Learning in Medical Imaging - 6th International Workshop, 2015

Learning optimal striking points for a ping-pong playing robot.
Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015

Identification of Time-Dependent Causal Model: A Gaussian Process Treatment.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Telling cause from effect in deterministic linear dynamical systems.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Removing systematic errors for exoplanet search via latent causes.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Towards a Learning Theory of Cause-Effect Inference.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Retrospective Motion Correction of Magnitude-Input MR Images.
Proceedings of the Machine Learning Meets Medical Imaging - First International Workshop, 2015

Discovering Temporal Causal Relations from Subsampled Data.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Causal Inference by Identification of Vector Autoregressive Processes with Hidden Components.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Self-Calibration of Optical Lenses.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Brain-computer interfacing in amyotrophic lateral sclerosis: Implications of a resting-state EEG analysis.
Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2015

Identification of the Default Mode Network with electroencephalography.
Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2015

Inference of Cause and Effect with Unsupervised Inverse Regression.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Multi-Source Domain Adaptation: A Causal View.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Cost-Sensitive Active Learning With Lookahead: Optimizing Field Surveys for Remote Sensing Data Classification.
IEEE Trans. Geoscience and Remote Sensing, 2014

Uncovering the structure and temporal dynamics of information propagation.
Network Science, 2014

Causal Discovery via Reproducing Kernel Hilbert Space Embeddings.
Neural Computation, 2014

Causal discovery with continuous additive noise models.
Journal of Machine Learning Research, 2014

Learning strategies in table tennis using inverse reinforcement learning.
Biological Cybernetics, 2014

Estimating Causal Effects by Bounding Confounding.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

A Permutation-Based Kernel Conditional Independence Test.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Inferring latent structures via information inequalities.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Causal and anti-causal learning in pattern recognition for neuroimaging.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2014

Kernel Mean Estimation via Spectral Filtering.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Quantifying Information Overload in Social Media and Its Impact on Social Contagions.
Proceedings of the Eighth International Conference on Weblogs and Social Media, 2014

Kernel Mean Estimation and Stein Effect.
Proceedings of the 31th International Conference on Machine Learning, 2014

Randomized Nonlinear Component Analysis.
Proceedings of the 31th International Conference on Machine Learning, 2014

Consistency of Causal Inference under the Additive Noise Model.
Proceedings of the 31th International Conference on Machine Learning, 2014

Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm.
Proceedings of the 31th International Conference on Machine Learning, 2014

Mask-Specific Inpainting with Deep Neural Networks.
Proceedings of the Pattern Recognition - 36th German Conference, 2014

Seeing the Arrow of Time.
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

Open Problem: Finding Good Cascade Sampling Processes for the Network Inference Problem.
Proceedings of The 27th Conference on Learning Theory, 2014

Decoding index finger position from EEG using random forests.
Proceedings of the 4th International Workshop on Cognitive Information Processing, 2014

Towards building a Crowd-Sourced Sky Map.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013
Probabilistic movement modeling for intention inference in human-robot interaction.
I. J. Robotics Res., 2013

HiFiVE: A Hilbert Space Embedding of Fiber Variability Estimates for Uncertainty Modeling and Visualization.
Comput. Graph. Forum, 2013

Structure and dynamics of information pathways in online media.
Proceedings of the Sixth ACM International Conference on Web Search and Data Mining, 2013

Identifying Finite Mixtures of Nonparametric Product Distributions and Causal Inference of Confounders.
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

One-Class Support Measure Machines for Group Anomaly Detection.
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

From Ordinary Differential Equations to Structural Causal Models: the deterministic case.
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

How to Test the Quality of Reconstructed Sources in Independent Component Analysis (ICA) of EEG/MEG Data.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2013

Causal Inference on Time Series using Restricted Structural Equation Models.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

The Randomized Dependence Coefficient.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Statistical analysis of coupled time series with Kernel Cross-Spectral Density operators.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Domain Adaptation under Target and Conditional Shift.
Proceedings of the 30th International Conference on Machine Learning, 2013

Domain Generalization via Invariant Feature Representation.
Proceedings of the 30th International Conference on Machine Learning, 2013

Modeling Information Propagation with Survival Theory.
Proceedings of the 30th International Conference on Machine Learning, 2013

Improving alpha matting and motion blurred foreground estimation.
Proceedings of the IEEE International Conference on Image Processing, 2013

On Estimation of Functional Causal Models: Post-Nonlinear Causal Model as an Example.
Proceedings of the 13th IEEE International Conference on Data Mining Workshops, 2013

A Machine Learning Approach for Non-blind Image Deconvolution.
Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

On a Link Between Kernel Mean Maps and Fraunhofer Diffraction, with an Application to Super-Resolution Beyond the Diffraction Limit.
Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

On the Relations and Differences Between Popper Dimension, Exclusion Dimension and VC-Dimension.
Proceedings of the Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik, 2013

Semi-supervised Learning in Causal and Anticausal Settings.
Proceedings of the Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik, 2013

Nonparametric dynamics estimation for time periodic systems.
Proceedings of the 51st Annual Allerton Conference on Communication, 2013

2012
A Kernel Two-Sample Test.
Journal of Machine Learning Research, 2012

Information-geometric approach to inferring causal directions.
Artif. Intell., 2012

Probabilistic Modeling of Human Movements for Intention Inference.
Proceedings of the Robotics: Science and Systems VIII, 2012

Learning from Distributions via Support Measure Machines.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Semi-Supervised Domain Adaptation with Non-Parametric Copulas.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

The representer theorem for Hilbert spaces: a necessary and sufficient condition.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

A brain-robot interface for studying motor learning after stroke.
Proceedings of the 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012

On causal and anticausal learning.
Proceedings of the 29th International Conference on Machine Learning, 2012

Submodular Inference of Diffusion Networks from Multiple Trees.
Proceedings of the 29th International Conference on Machine Learning, 2012

Influence Maximization in Continuous Time Diffusion Networks.
Proceedings of the 29th International Conference on Machine Learning, 2012

A blind deconvolution approach for pseudo CT prediction from MR image pairs.
Proceedings of the 19th IEEE International Conference on Image Processing, 2012

Blind Correction of Optical Aberrations.
Proceedings of the Computer Vision - ECCV 2012, 2012

Recording and Playback of Camera Shake: Benchmarking Blind Deconvolution with a Real-World Database.
Proceedings of the Computer Vision - ECCV 2012, 2012

2011
Statistical Learning Theory: Models, Concepts, and Results.
Proceedings of the Inductive Logic, 2011

Causal Inference on Discrete Data Using Additive Noise Models.
IEEE Trans. Pattern Anal. Mach. Intell., 2011

Causal influence of gamma oscillations on the sensorimotor rhythm.
NeuroImage, 2011

A Graphical Model Framework for Decoding in the Visual ERP-Based BCI Speller.
Neural Computation, 2011

Multi-way set enumeration in weight tensors.
Machine Learning, 2011

A Blind Deconvolution Approach for Improving the Resolution of Cryo-EM Density Maps.
Journal of Computational Biology, 2011

Kernel-based Conditional Independence Test and Application in Causal Discovery.
Proceedings of the UAI 2011, 2011

Identifiability of Causal Graphs using Functional Models.
Proceedings of the UAI 2011, 2011

Detecting low-complexity unobserved causes.
Proceedings of the UAI 2011, 2011

On Causal Discovery with Cyclic Additive Noise Models.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Two-locus association mapping in subquadratic time.
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

Learning anticipation policies for robot table tennis.
Proceedings of the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2011

Learning inverse kinematics with structured prediction.
Proceedings of the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2011

Uncovering the Temporal Dynamics of Diffusion Networks.
Proceedings of the 28th International Conference on Machine Learning, 2011

Support Vector Machines as Probabilistic Models.
Proceedings of the 28th International Conference on Machine Learning, 2011

Non-stationary correction of optical aberrations.
Proceedings of the IEEE International Conference on Computer Vision, 2011

Fast removal of non-uniform camera shake.
Proceedings of the IEEE International Conference on Computer Vision, 2011

Removing noise from astronomical images using a pixel-specific noise model.
Proceedings of the 2011 IEEE International Conference on Computational Photography, 2011

Finding dependencies between frequencies with the kernel cross-spectral density.
Proceedings of the IEEE International Conference on Acoustics, 2011

2010
Causal inference using the algorithmic Markov condition.
IEEE Trans. Information Theory, 2010

Nonparametric Regression between General Riemannian Manifolds.
SIAM J. Imaging Sciences, 2010

Remote Sensing Feature Selection by Kernel Dependence Measures.
IEEE Geosci. Remote Sensing Lett., 2010

Hilbert Space Embeddings and Metrics on Probability Measures.
Journal of Machine Learning Research, 2010

Identifying Cause and Effect on Discrete Data using Additive Noise Models.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Causality: Objectives and Assessment.
Proceedings of the Causality: Objectives and Assessment (NIPS 2008 Workshop), 2010

Causal relationships between frequency bands of extracellular signals in visual cortex revealed by an information theoretic analysis.
Journal of Computational Neuroscience, 2010

Invariant Gaussian Process Latent Variable Models and Application in Causal Discovery.
Proceedings of the UAI 2010, 2010

Inferring deterministic causal relations.
Proceedings of the UAI 2010, 2010

Closing the sensorimotor loop: Haptic feedback facilitates decoding of arm movement imagery.
Proceedings of the IEEE International Conference on Systems, 2010

A New Algorithm for Improving the Resolution of Cryo-EM Density Maps.
Proceedings of the Research in Computational Molecular Biology, 2010

Probabilistic latent variable models for distinguishing between cause and effect.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Switched Latent Force Models for Movement Segmentation.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Non-parametric estimation of integral probability metrics.
Proceedings of the IEEE International Symposium on Information Theory, 2010

The Influence of the Image Basis on Modeling and Steganalysis Performance.
Proceedings of the Information Hiding - 12th International Conference, 2010

Movement templates for learning of hitting and batting.
Proceedings of the IEEE International Conference on Robotics and Automation, 2010

Telling cause from effect based on high-dimensional observations.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Multiframe blind deconvolution, super-resolution, and saturation correction via incremental EM.
Proceedings of the International Conference on Image Processing, 2010

Efficient filter flow for space-variant multiframe blind deconvolution.
Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

Causal Markov Condition for Submodular Information Measures.
Proceedings of the COLT 2010, 2010

2009
Prototype Classification: Insights from Machine Learning.
Neural Computation, 2009

Protein functional class prediction with a combined graph.
Expert Syst. Appl., 2009

Identifying confounders using additive noise models.
Proceedings of the UAI 2009, 2009

Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Generalized Clustering via Kernel Embeddings.
Proceedings of the KI 2009: Advances in Artificial Intelligence, 2009

Multi-way set enumeration in real-valued tensors.
Proceedings of the 2nd ACM SIGKDD Workshop on Data Mining using Matrices and Tensors, 2009

Sparse online model learning for robot control with support vector regression.
Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009

Detecting the direction of causal time series.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Regression by dependence minimization and its application to causal inference in additive noise models.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

09401 Abstracts Collection - Machine learning approaches to statistical dependences and causality.
Proceedings of the Machine learning approaches to statistical dependences and causality, 27.09., 2009

Markerless 3D Face Tracking.
Proceedings of the Pattern Recognition, 2009

Learning similarity measure for multi-modal 3D image registration.
Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), 2009

2008
Kernels, regularization and differential equations.
Pattern Recognition, 2008

Support Vector Machines and Kernels for Computational Biology.
PLoS Computational Biology, 2008

Causal reasoning by evaluating the complexity of conditional densities with kernel methods.
Neurocomputing, 2008

Guest Editorial.
International Journal of Computer Vision, 2008

Manifold-valued Thin-Plate Splines with Applications in Computer Graphics.
Comput. Graph. Forum, 2008

Diffeomorphic Dimensionality Reduction.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Bayesian Experimental Design of Magnetic Resonance Imaging Sequences.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

An Empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence Analysis.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Nonlinear causal discovery with additive noise models.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Characteristic Kernels on Groups and Semigroups.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Sparse multiscale gaussian process regression.
Proceedings of the Machine Learning, 2008

Tailoring density estimation via reproducing kernel moment matching.
Proceedings of the Machine Learning, 2008

Kernel Methods for Detecting the Direction of Time Series.
Proceedings of the Advances in Data Analysis, Data Handling and Business Intelligence, 2008

Automatic 3D face reconstruction from single images or video.
Proceedings of the 8th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2008), 2008

Learning Inverse Dynamics: a Comparison.
Proceedings of the ESANN 2008, 2008

Automatic Image Colorization Via Multimodal Predictions.
Proceedings of the Computer Vision, 2008

Injective Hilbert Space Embeddings of Probability Measures.
Proceedings of the 21st Annual Conference on Learning Theory, 2008

2007
Real-Time Fetal Heart Monitoring in Biomagnetic Measurements Using Adaptive Real-Time ICA.
IEEE Trans. Biomed. Engineering, 2007

Feature Selection for Troubleshooting in Complex Assembly Lines.
IEEE Trans. Automation Science and Engineering, 2007

Improving the Caenorhabditis elegans Genome Annotation Using Machine Learning.
PLoS Computational Biology, 2007

Transductive Classification via Local Learning Regularization.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

The Need for Open Source Software in Machine Learning.
Journal of Machine Learning Research, 2007

An Analysis of Inference with the Universum.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

A Kernel Statistical Test of Independence.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Kernel Measures of Conditional Dependence.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Local learning projections.
Proceedings of the Machine Learning, 2007

A kernel-based causal learning algorithm.
Proceedings of the Machine Learning, 2007

Distinguishing between cause and effect via kernel-based complexity measures for conditional distributions.
Proceedings of the ESANN 2007, 2007

A Hilbert Space Embedding for Distributions.
Proceedings of the Discovery Science, 10th International Conference, 2007

How to Find Interesting Locations in Video: A Spatiotemporal Interest Point Detector Learned from Human Eye Movements.
Proceedings of the Pattern Recognition, 2007

Towards Machine Learning of Motor Skills.
Proceedings of the Autonome Mobile Systeme 2007, 2007

A Hilbert Space Embedding for Distributions.
Proceedings of the Algorithmic Learning Theory, 18th International Conference, 2007

A Kernel Approach to Comparing Distributions.
Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, 2007

2006
Classification of Faces in Man and Machine.
Neural Computation, 2006

A Unifying View of Wiener and Volterra Theory and Polynomial Kernel Regression.
Neural Computation, 2006

A Direct Method for Building Sparse Kernel Learning Algorithms.
Journal of Machine Learning Research, 2006

Large Scale Multiple Kernel Learning.
Journal of Machine Learning Research, 2006

Implicit Surface Modelling with a Globally Regularised Basis of Compact Support.
Comput. Graph. Forum, 2006

Learning with Hypergraphs: Clustering, Classification, and Embedding.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

A Local Learning Approach for Clustering.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Implicit Surfaces with Globally Regularised and Compactly Supported Basis Functions.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Learning Dense 3D Correspondence.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

A Nonparametric Approach to Bottom-Up Visual Saliency.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Correcting Sample Selection Bias by Unlabeled Data.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

A Kernel Method for the Two-Sample-Problem.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Integrating structured biological data by Kernel Maximum Mean Discrepancy.
Proceedings of the Proceedings 14th International Conference on Intelligent Systems for Molecular Biology 2006, 2006

Causal Inference by Choosing Graphs with Most Plausible Markov Kernels.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2006

Classifying Event-Related Desynchronization in EEG, ECoG and MEG Signals.
Proceedings of the Pattern Recognition, 2006

Learning an Interest Operator from Human Eye Movements.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2006

2005
Iterative Kernel Principal Component Analysis for Image Modeling.
IEEE Trans. Pattern Anal. Mach. Intell., 2005

Experimentally optimal nu in support vector regression for different noise models and parameter settings.
Neural Networks, 2005

Kernel Methods for Measuring Independence.
Journal of Machine Learning Research, 2005

Maximal margin classification for metric spaces.
J. Comput. Syst. Sci., 2005

Robust EEG Channel Selection across Subjects for Brain-Computer Interfaces.
EURASIP J. Adv. Sig. Proc., 2005

Support Vector Machines for 3D Shape Processing.
Comput. Graph. Forum, 2005

Evaluating Predictive Uncertainty Challenge.
Proceedings of the Machine Learning Challenges, 2005

Joint Kernel Maps.
Proceedings of the Computational Intelligence and Bioinspired Systems, 2005

Long Term Prediction of Product Quality in a Glass Manufacturing Process Using a Kernel Based Approach.
Proceedings of the Computational Intelligence and Bioinspired Systems, 2005

RASE: recognition of alternatively spliced exons in C.elegans.
Proceedings of the Proceedings Thirteenth International Conference on Intelligent Systems for Molecular Biology 2005, 2005

Learning from labeled and unlabeled data on a directed graph.
Proceedings of the Machine Learning, 2005

Building Sparse Large Margin Classifiers.
Proceedings of the Machine Learning, 2005

Implicit surface modelling as an eigenvalue problem.
Proceedings of the Machine Learning, 2005

Large scale genomic sequence SVM classifiers.
Proceedings of the Machine Learning, 2005

Object correspondence as a machine learning problem.
Proceedings of the Machine Learning, 2005

A brain computer interface with online feedback based on magnetoencephalography.
Proceedings of the Machine Learning, 2005

Training Support Vector Machines with Multiple Equality Constraints.
Proceedings of the Machine Learning: ECML 2005, 2005

Fast protein classification with multiple networks.
Proceedings of the ECCB/JBI'05 Proceedings, Fourth European Conference on Computational Biology/Sixth Meeting of the Spanish Bioinformatics Network (Jornadas de BioInformática), Palacio de Congresos, Madrid, Spain, September 28, 2005

Regularization on Discrete Spaces.
Proceedings of the Pattern Recognition, 27th DAGM Symposium, Vienna, Austria, August 31, 2005

Measuring Statistical Dependence with Hilbert-Schmidt Norms.
Proceedings of the Algorithmic Learning Theory, 16th International Conference, 2005

Kernel Constrained Covariance for Dependence Measurement.
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

2004
Support vector channel selection in BCI.
IEEE Trans. Biomed. Engineering, 2004

A tutorial on support vector regression.
Statistics and Computing, 2004

Experimentally optimal v in support vector regression for different noise models and parameter settings.
Neural Networks, 2004

A Compression Approach to Support Vector Model Selection.
Journal of Machine Learning Research, 2004

Feature Selection for Support Vector Machines Using Genetic Algorithms.
International Journal on Artificial Intelligence Tools, 2004

Semi-supervised Learning on Directed Graphs.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Machine Learning Applied to Perception: Decision Images for Gender Classification.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Kernel Methods for Implicit Surface Modeling.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Methods Towards Invasive Human Brain Computer Interfaces.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Face Detection - Efficient and Rank Deficient.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

An Auditory Paradigm for Brain-Computer Interfaces.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Implicit Wiener Series for Higher-Order Image Analysis.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

A kernel view of the dimensionality reduction of manifolds.
Proceedings of the Machine Learning, 2004

Learning from Labeled and Unlabeled Data Using Random Walks.
Proceedings of the Pattern Recognition, 26th DAGM Symposium, August 30, 2004

Efficient Approximations for Support Vector Machines in Object Detection.
Proceedings of the Pattern Recognition, 26th DAGM Symposium, August 30, 2004

Semi-supervised Kernel Regression Using Whitened Function Classes.
Proceedings of the Pattern Recognition, 26th DAGM Symposium, August 30, 2004

Multivariate Regression via Stiefel Manifold Constraints.
Proceedings of the Pattern Recognition, 26th DAGM Symposium, August 30, 2004

2003
Constructing Descriptive and Discriminative Nonlinear Features: Rayleigh Coefficients in Kernel Feature Spaces.
IEEE Trans. Pattern Anal. Mach. Intell., 2003

Use of the Zero-Norm with Linear Models and Kernel Methods.
Journal of Machine Learning Research, 2003

Statistical learning theory, capacity, and complexity.
Complexity, 2003

Feature selection and transduction for prediction of molecular bioactivity for drug design.
Bioinformatics, 2003

Ranking on Data Manifolds.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Learning with Local and Global Consistency.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Prediction on Spike Data Using Kernel Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Learning to Find Pre-Images.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Feature Selection for Support Vector Machines by Means of Genetic Algorithms.
Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2003), 2003

2002
Constructing Boosting Algorithms from SVMs: An Application to One-Class Classification.
IEEE Trans. Pattern Anal. Mach. Intell., 2002

Training Invariant Support Vector Machines.
Machine Learning, 2002

Support Vector Machines and Kernel Methods: The New Generation of Learning Machines.
AI Magazine, 2002

A Kernel Approach for Learning from Almost Orthogonal Patterns.
Proceedings of the Principles of Data Mining and Knowledge Discovery, 2002

Kernel Dependency Estimation.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Cluster Kernels for Semi-Supervised Learning.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Bayesian Kernel Methods.
Proceedings of the Advanced Lectures on Machine Learning, 2002

A Short Introduction to Learning with Kernels.
Proceedings of the Advanced Lectures on Machine Learning, 2002

A Kernel Approach for Learning from almost Orthogonal Patterns.
Proceedings of the Machine Learning: ECML 2002, 2002

Learning with Kernels: support vector machines, regularization, optimization, and beyond.
Adaptive computation and machine learning series, MIT Press, ISBN: 9780262194754, 2002

2001
An introduction to kernel-based learning algorithms.
IEEE Trans. Neural Networks, 2001

Generalization performance of regularization networks and support vector machines via entropy numbers of compact operators.
IEEE Trans. Information Theory, 2001

Estimating the Support of a High-Dimensional Distribution.
Neural Computation, 2001

Regularized Principal Manifolds.
Journal of Machine Learning Research, 2001

Incorporating Invariances in Non-Linear Support Vector Machines.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Sampling Techniques for Kernel Methods.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Estimating a Kernel Fisher Discriminant in the Presence of Label Noise.
Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001

Computationally Efficient Face Detection.
ICCV, 2001

Kernel Machine Based Learning for Multi-View Face Detection and Pose Estimation.
ICCV, 2001

A Generalized Representer Theorem.
Proceedings of the Computational Learning Theory, 2001

A Kernel Approach for Vector Quantization with Guaranteed Distortion Bounds.
Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001

An improved training algorithm for kernel Fisher discriminants.
Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001

2000
New Support Vector Algorithms.
Neural Computation, 2000

Engineering support vector machine kernels that recognize translation initiation sites.
Bioinformatics, 2000

Robust Ensemble Learning for Data Mining.
Proceedings of the Knowledge Discovery and Data Mining, 2000

Four-legged Walking Gait Control Using a Neuromorphic Chip Interfaced to a Support Vector Learning Algorithm.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

The Kernel Trick for Distances.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

Choosing in Support Vector Regression with Different Noise Models: Theory and Experiments.
IJCNN (5), 2000

Sparse Greedy Matrix Approximation for Machine Learning.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

Entropy Numbers of Linear Function Classes.
Proceedings of the Thirteenth Annual Conference on Computational Learning Theory (COLT 2000), June 28, 2000

1999
Input space versus feature space in kernel-based methods.
IEEE Trans. Neural Networks, 1999

Lernen mit Kernen: Support-Vektor-Methoden zur Analyse hochdimensionaler Daten.
Inform., Forsch. Entwickl., 1999

The Entropy Regularization Information Criterion.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Support Vector Method for Novelty Detection.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

v-Arc: Ensemble Learning in the Presence of Outliers.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Invariant Feature Extraction and Classification in Kernel Spaces.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Engineering Support Vector Machine Kerneis That Recognize Translation Initialion Sites.
German Conference on Bioinformatics, 1999

Entropy Numbers, Operators and Support Vector Kernels.
Proceedings of the Computational Learning Theory, 4th European Conference, 1999

Regularized Principal Manifolds.
Proceedings of the Computational Learning Theory, 4th European Conference, 1999

1998
The connection between regularization operators and support vector kernels.
Neural Networks, 1998

Nonlinear Component Analysis as a Kernel Eigenvalue Problem.
Neural Computation, 1998

Where did I take that snapshot? Scene-based homing by image matching.
Biological Cybernetics, 1998

Learning View Graphs for Robot Navigation.
Auton. Robots, 1998

On a Kernel-Based Method for Pattern Recognition, Regression, Approximation, and Operator Inversion.
Algorithmica, 1998

Semiparametric Support Vector and Linear Programming Machines.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Shrinking the Tube: A New Support Vector Regression Algorithm.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Kernel PCA and De-Noising in Feature Spaces.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Fast Approximation of Support Vector Kernel Expansions, and an Interpretation of Clustering as Approximation in Feature Spaces.
Proceedings of the Mustererkennung 1998, 20. DAGM-Symposium, Stuttgart, 29. September, 1998

Navigation mit Schnappschüssen.
Proceedings of the Mustererkennung 1998, 20. DAGM-Symposium, Stuttgart, 29. September, 1998

1997
Support vector learning.
PhD thesis, 1997

Comparing support vector machines with Gaussian kernels to radial basis function classifiers.
IEEE Trans. Signal Processing, 1997

From Regularization Operators to Support Vector Kernels.
Proceedings of the Advances in Neural Information Processing Systems 10, 1997

Prior Knowledge in Support Vector Kernels.
Proceedings of the Advances in Neural Information Processing Systems 10, 1997

Kernel Principal Component Analysis.
Proceedings of the Artificial Neural Networks, 1997

Predicting Time Series with Support Vector Machines.
Proceedings of the Artificial Neural Networks, 1997

The View-Graph Approach to Visual Navigation and Spatial Memory.
Proceedings of the Artificial Neural Networks, 1997

Learning View Graphs for Robot Navigation.
Proceedings of the First International Conference on Autonomous Agents, 1997

1996
Improving the Accuracy and Speed of Support Vector Machines.
Proceedings of the Advances in Neural Information Processing Systems 9, 1996

Incorporating Invariances in Support Vector Learning Machines.
Proceedings of the Artificial Neural Networks, 1996

Comparison of View-Based Object Recognition Algorithms Using Realistic 3D Models.
Proceedings of the Artificial Neural Networks, 1996

1995
View-Based Cognitive Mapping and Path Planning.
Adaptive Behaviour, 1995

Extracting Support Data for a Given Task.
Proceedings of the First International Conference on Knowledge Discovery and Data Mining (KDD-95), 1995


  Loading...