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SUMMARY:Causality-Inspired Machine Learning: A Path to More Robust AI Syst
 ems -  Prof Peter Bühlmann (ETH Zurich)
DTSTART:20250508T110000Z
DTEND:20250508T120000Z
UID:TALK212089@talks.cam.ac.uk
CONTACT:HoD Secretary\, DPMMS
DESCRIPTION:\nThe pursuit of reliable and robust machine learning has beco
 me a central focus\, with statistics and data science playing pivotal role
 s in its advancement. We explore connections between distributional robust
 ness and causality\, providing methodological insights to enhance the reli
 ability of AI systems. We examine the broader implications of these concep
 ts through a case study in digital health and emphasize the crucial need f
 or validating machine learning and AI algorithms in real-world application
 s. 
LOCATION:Cockcroft Lecture Theatre\, New Museums Site
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