NIPS Proceedings^β

Bernhard Schölkopf

57 Papers

Kernel Mean Estimation via Spectral Filtering (2014)

Causal Inference on Time Series using Restricted Structural Equation Models (2013)

Statistical analysis of coupled time series with Kernel Cross-Spectral Density operators. (2013)

The Randomized Dependence Coefficient (2013)

Learning from Distributions via Support Measure Machines (2012)

Semi-Supervised Domain Adaptation with Non-Parametric Copulas (2012)

The representer theorem for Hilbert spaces: a necessary and sufficient condition (2012)

On Causal Discovery with Cyclic Additive Noise Models (2011)

Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance (2011)

Probabilistic latent variable models for distinguishing between cause and effect (2010)

Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake (2010)

Switched Latent Force Models for Movement Segmentation (2010)

Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions (2009)

An Empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence Analysis (2008)

Bayesian Experimental Design of Magnetic Resonance Imaging Sequences (2008)

Characteristic Kernels on Groups and Semigroups (2008)

Diffeomorphic Dimensionality Reduction (2008)

Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance (2008)

Nonlinear causal discovery with additive noise models (2008)

A Kernel Statistical Test of Independence (2007)

An Analysis of Inference with the Universum (2007)

Kernel Measures of Conditional Dependence (2007)

A Kernel Method for the Two-Sample-Problem (2006)

A Local Learning Approach for Clustering (2006)

A Nonparametric Approach to Bottom-Up Visual Saliency (2006)

Correcting Sample Selection Bias by Unlabeled Data (2006)

Implicit Surfaces with Globally Regularised and Compactly Supported Basis Functions (2006)

Learning Dense 3D Correspondence (2006)

Learning with Hypergraphs: Clustering, Classification, and Embedding (2006)

An Auditory Paradigm for Brain-Computer Interfaces (2004)

Face Detection --- Efficient and Rank Deficient (2004)

Implicit Wiener Series for Higher-Order Image Analysis (2004)

Kernel Methods for Implicit Surface Modeling (2004)

Machine Learning Applied to Perception: Decision Images for Gender Classification (2004)

Methods Towards Invasive Human Brain Computer Interfaces (2004)

Semi-supervised Learning on Directed Graphs (2004)

Learning to Find Pre-Images (2003)

Learning with Local and Global Consistency (2003)

Prediction on Spike Data Using Kernel Algorithms (2003)

Ranking on Data Manifolds (2003)

Cluster Kernels for Semi-Supervised Learning (2002)

Kernel Dependency Estimation (2002)

Incorporating Invariances in Non-Linear Support Vector Machines (2001)

Sampling Techniques for Kernel Methods (2001)

Four-legged Walking Gait Control Using a Neuromorphic Chip Interfaced to a Support Vector Learning Algorithm (2000)

Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra (2000)

The Kernel Trick for Distances (2000)

Invariant Feature Extraction and Classification in Kernel Spaces (1999)

Support Vector Method for Novelty Detection (1999)

The Entropy Regularization Information Criterion (1999)

v-Arc: Ensemble Learning in the Presence of Outliers (1999)

Kernel PCA and De-Noising in Feature Spaces (1998)

Semiparametric Support Vector and Linear Programming Machines (1998)

Shrinking the Tube: A New Support Vector Regression Algorithm (1998)

From Regularization Operators to Support Vector Kernels (1997)

Prior Knowledge in Support Vector Kernels (1997)

Improving the Accuracy and Speed of Support Vector Machines (1996)

3 Books

Advances in Neural Information Processing Systems 19 (2006)

Advances in Neural Information Processing Systems 18 (2005)

Advances in Neural Information Processing Systems 16 (2003)