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X-WR-CALDESC:FAU DCN-AvH. Chair for Dynamics, Control, Machine Learning and Numerics -Alexander von Humboldt Professorship
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DTSTART:20260329T030000
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DTSTART;TZID=Europe/Berlin:20201210T140000
DTEND;TZID=Europe/Berlin:20201210T150000
DTSTAMP:20211020T084821Z
CREATED:20211020
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SUMMARY:Turnpike Control and Deep Learning
DESCRIPTION:Worldwide. This Thursday December 10th. our Head Enrique Zuazua ( https://www.dcn.nat.fau.eu/zuazua ) will be talking about “Turnpike control and deep learning”, a seminar organized by the MOX Politecnico di Milano. ( https://mox.polimi.it/ )\nThe turnpike principle, ubiquitous in applications, asserts that in long time horizons optimal control strategies are nearly of a steady state nature. In this lecture we shall survey on some recent results on this topic and present some its consequences on deep supervised learning, and, in particular, in Residual Neural Networks.\nThis lecture is based on joint work with our team member Carlos Esteve ( https://cmc.deusto.eus/carlos-esteve-yague/ ), Borjan Geshkovski ( https://cmc.deusto.eus/borjan-geshkovski/ ) and Dario Pighin ( https://cmc.deusto.eus/dario-pighin/ ).\n \nWHEN?\nDecember 10th at 14:00H\nJOIN THIS SESSION VIA ZOOM (link 5mins before session)\nSee more details at the MOX’s event page\n
URL:https://dcn.nat.fau.eu/events/turnpike-control-and-deep-learning/
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CATEGORIES:EZuazua,Seminar/Talk
LOCATION:Worldwide
ATTACH;FMTTYPE=image/png:https://dcn.nat.fau.eu/wp-content/uploads/seminar-ezuazua-mox-10dic2020.png
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