1968–, Computer scientist
Bernhard Schölkopf is a German computer scientist who has been a leading figure in the development of kernel methods and, more recently, of causal machine learning. With Vladimir Vapnik and Alex Smola he co-authored Learning with Kernels (2001), the standard textbook of the field. He has contributed to kernel principal component analysis, to support-vector regression, and to the theory of representer theorems.
Schölkopf is a founding director of the Max Planck Institute for Intelligent Systems in Tübingen, one of Europe's leading machine-learning research centres. His more recent work on causal inference for machine learning, including connections between causality and out-of-distribution generalisation, has been influential in the post-deep-learning research community.
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Related people: Vladimir Vapnik
Discussed in:
- Chapter 6: ML Fundamentals, Machine Learning Fundamentals