In machine learning, we use data to automatically find dependences in the world, with the goal of predicting future observations. Most machine learning methods build on statistics, but one can also try to go beyond this, assaying causal structures underlying statistical dependences. The hope is that this also allows prediction in certain situations where systems change, for instance by interventions.
The talk will introduce the basic ideas of machine learning, and illustrate them with application examples. It argues that while machine learning and "big data" analysis currently mainly focuses on statistics; the causal point of view can provide additional insights.
Professor Bernhard Schölkopf is based at the Max Planck Institute for Intelligent Systems in Germany. He was given the 2014 Royal Society Milner Award in recognition of his pioneering work in machine learning which defined the field of “kernel machines”, now widely used in all areas of science and industry.
Information on participating / attending:
Eintritt frei
Date:
11/27/2014 18:30 - 11/27/2014 19:30
Event venue:
The Royal Society, London
6-9 Carlton House Terrace
London SW1Y 5AG
+44 (0)20 7451 2500
https://royalsociety.org/visit-us/london/
SW1Y 5AG London
United Kingdom
Target group:
Journalists, Scientists and scholars
Email address:
Relevance:
international
Subject areas:
Information technology, Mathematics
Types of events:
Presentation / colloquium / lecture
Entry:
11/25/2014
Sender/author:
Claudia Däfler
Department:
Public Relations - Standort Tübingen
Event is free:
yes
Language of the text:
German
URL of this event: http://idw-online.de/en/event49262
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