BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:Microsoft Distinguished Research Lecture: Toward Causal Machine Le
 arning - Prof. Dr. Bernhard Schölkopf
DTSTART:20150515T154500Z
DTEND:20150515T164500Z
UID:TALK58951@talks.cam.ac.uk
CONTACT:41807
DESCRIPTION:In machine learning\, we use data to automatically find depend
 ences 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 dependenc
 es. Can such causal knowledge help prediction in machine learning tasks? W
 e argue that this is indeed the case\, due to the fact that causal models 
 are more robust to changes that occur in real world datasets. We touch upo
 n the implications of causal models for machine learning tasks such as dom
 ain adaptation\, transfer learning\, and semi-supervised learning. We also
  present an application to the removal of systematic errors for the purpos
 e of exoplanet detection. \n\nMachine learning currently mainly focuses on
  relatively well-studied statistical methods. Some of the causal problems 
 are conceptually harder\, however\, the causal point of view can provide a
 dditional insights that have substantial potential for data analysis.\n\nP
 lease register for this talk to ensure your place: http://research.microso
 ft.com/en-us/events/msdrl/tcml.aspx 
LOCATION:Auditorium\, Microsoft Research Ltd\, 21 Station Road\, Cambridge
 \, CB1 2FB
END:VEVENT
END:VCALENDAR