BEGIN:VCALENDAR
VERSION:2.0
PRODID:researchseminars.org
CALSCALE:GREGORIAN
X-WR-CALNAME:researchseminars.org
BEGIN:VEVENT
SUMMARY:Dan Roberts (MIT\, Center for Theoretical Physics)
DTSTART:20220113T170000Z
DTEND:20220113T180000Z
DTSTAMP:20260423T003246Z
UID:MPML/63
DESCRIPTION:Title: <a href="https://researchseminars.org/talk/MPML/63/">Th
 e Principles of Deep Learning Theory</a>\nby Dan Roberts (MIT\, Center for
  Theoretical Physics) as part of Mathematics\, Physics and Machine Learnin
 g (IST\, Lisbon)\n\n\nAbstract\nDeep learning is an exciting approach to m
 odern artificial intelligence based on artificial neural networks. The goa
 l of this talk is to provide a blueprint — using tools from physics — 
 for theoretically analyzing deep neural networks of practical relevance. T
 his task will encompass both understanding the statistics of initialized d
 eep networks and determining the training dynamics of such an ensemble whe
 n learning from data.\n\nThis talk is based on a book\, <a href="https://a
 rxiv.org/pdf/2106.10165.pdf">"The Principles of Deep Learning Theory\,"</a
 > co-authored with Sho Yaida and based on research also in collaboration w
 ith Boris Hanin. It will be published next year by Cambridge University Pr
 ess.\n
LOCATION:https://researchseminars.org/talk/MPML/63/
END:VEVENT
END:VCALENDAR