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Turnpike Control and Deep Learning

Worldwide. This Thursday December 10th. our Head Enrique Zuazua will be talking about “Turnpike control and deep learning”, a seminar organized by the MOX Politecnico di Milano.

The 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.

This lecture is based on joint work with our team member Carlos Esteve, Borjan Geshkovski and Dario Pighin.


December 10th at 14:00H


(link 5min before session)
See more details at the MOX’s event page

The event is finished.


Thu 10th Dec 2020


2:00 pm - 3:00 pm

Local Time

  • Timezone: America/New_York
  • Date: Thu 10th Dec 2020
  • Time: 8:00 am - 9:00 am


Seminar | Talk (external)


  • Enrique Zuazua
    Enrique Zuazua
    Alexander von Humboldt Professorship | Head of the Chair of Computational Mathematics | Professor of Applied Mathematics

    Enrique Zuazua (Eibar, Basque Country – Spain, 1961) holds an Alexander von Humboldt Professorship at the Friedrich–Alexander University (FAU), Erlangen (Germany). He is also the Director of the Chair of Computational Mathematics at Deusto Foundation, Universidad de Deusto (Bilbao, Basque Country-Spain) where he leads the research team funded by the ERC Advanced Grant DyCoN project. He is also a Professor of Applied Mathematics since 2001 at the Department of Mathematics of the Autonomous University of Madrid where he holds a Strategic Chair.
    more about Enrique

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