Bernhard Schölkopf | Researcher Profile | Sotabase

Career

· Scientific Director, ELLIS Institute Tübingen2023–

· Affiliated Full Professor, ETH Zurich2019–

· Distinguished Scientist, Amazon2017–2023

· Director, Max Planck Institute for Intelligent Systems2011–

· Honorary Professor, TU Berlin2002–

· Director, Max Planck Institute for Biological Cybernetics2001–2010

· Group Leader, Biowulf Technologies2000–2001

· Researcher, Microsoft Research1999–2000

· Researcher, GMD (German National Research Center for Computer Science)1997–1999

· PhD in Computer Science, TU Berlin1997–

· Diplom in Physics, University of Tübingen1994–

· MSc in Mathematics, University of London1992–

· Honorary Professor, University of Tübingen

Publications (1209)

A tutorial on support vector regression

Statistics and computing · 2004

12,429

cited

Nonlinear Component Analysis as a Kernel Eigenvalue Problem

Neural Computation · 1998

8,722

cited

Estimating the Support of a High-Dimensional Distribution

Neural Computation · 2001

6,190

cited

A Kernel Two-Sample Test

Journal of machine learning research · 2012

5,889

cited

Advances in kernel methods: support vector learning

1999

5,533

cited

Learning with Kernels: support vector machines, regularization, optimization, and beyond

Adaptive computation and machine learning series · 2001

5,261

cited

Learning with Local and Global Consistency

Neural Information Processing Systems · 2003

4,584

cited

An introduction to kernel-based learning algorithms

IEEE Trans. Neural Networks · 2001

3,761

cited

Fisher discriminant analysis with kernels

Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop (Cat. No.98TH8468) · 1999

3,109

cited

New Support Vector Algorithms

Neural Computation · 2000

2,951

cited

Kernel Principal Component Analysis

International Conference on Artificial Neural Networks · 1997

2,684

cited

A gene expression map of Arabidopsis thaliana development

Nature Genetics · 2005

2,585

cited

Support Vector Method for Novelty Detection

Neural Information Processing Systems · 1999

2,554

cited

A Kernel Method for the Two-Sample-Problem

Neural Information Processing Systems · 2006

2,543

cited

Kernel methods in machine learning

2007

2,163

cited

A Generalized Representer Theorem

COLT/EuroCOLT · 2001

1,929

cited

Measuring Statistical Dependence with Hilbert-Schmidt Norms

International Conference on Algorithmic Learning Theory · 2005

1,900

cited

Correcting Sample Selection Bias by Unlabeled Data

Neural Information Processing Systems · 2006

1,877

cited

Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations

International Conference on Machine Learning · 2018

1,637

cited

Integrating structured biological data by Kernel Maximum Mean Discrepancy

Intelligent Systems in Molecular Biology · 2006

1,637

cited

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