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X-ORIGINAL-URL:https://cmc.deusto.eus/
X-WR-CALNAME:cmc.deusto.eus
X-WR-CALDESC:DeustoCCM - Chair of Computational Mathematics at University of Deusto
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BEGIN:VEVENT
CLASS:PUBLIC
UID:MEC-479065c78e0ba7c787a6cf9bcbc8c181@cmc.deusto.eus
DTSTART:20240219T160000Z
DTEND:20240219T165000Z
DTSTAMP:20251031T222800Z
CREATED:20251031
LAST-MODIFIED:20251031
PRIORITY:5
TRANSP:OPAQUE
SUMMARY:DEDS2024
DESCRIPTION:On Monday February 19, 2024, Prof. Enrique Zuazua ( http://dcn.nat.fau.eu/zuazua/ ) will talk on Control and Machine Learning at the DEDS2024, Differential Equations for Data Science 2024, the international conference organized (online) on February 19 – 21, 2024.\nAbstract. In this lecture we shall present some recent results on the interplay between control and Machine Learning, and more precisely, Supervised Learning and Universal Approximation.We adopt the perspective of the simultaneous or ensemble control of systems of Residual Neural Networks (ResNets). Roughly, each item to be classified corresponds to a different initial datum for the Cauchy problem of the ResNets, leading to an ensemble of solutions to be driven to the corresponding targets, associated to the labels, by means of the same control. \nWe present a genuinely nonlinear and constructive method, allowing to show that such an ambitious goal can be achieved, estimating the complexity of the control strategies. This property is rarely fulfilled by the classical dynamical systems in Mechanics and the very nonlinear nature of the activation function governing the ResNet dynamics plays a determinant role. It allows deforming half of the phase space while the other half remains invariant, a property that classical models in mechanics do not fulfill. This viewpoint opens up interesting perspectives to develop new hybrid mechanics-data driven modelling methodlogies. \nThis lecture is inspired in joint work, among others, with Borjan Geshkovski (MIT), Carlos Esteve (Cambridge), Domenec Ruiz-Balet (IC, London) and Dario Pighin (Sherpa.ai).\nThis conference is mainly devoted to new mathematical aspects on machine learning algorithms, big data analysis, and other topics in data science area, from a viewpoint of differential equations. In recent years, several interesting connections between differential equations and data science have been found and attract attention from researchers of differential equations. In this conference, we will gather such researchers of differential equations who have interest in data science and try to shed new light on mathematical foundations on the topics in machine learning/data science.\nWHEN\nMon. February 19, 2024 at 17:00H\nRegistration\nRegistration is free but mandatory to receive the zoom link: Registration form.\nIf the link does not work, copy and paste the following entire URL into your internet browser:\nhttps://us06web.zoom.us/meeting/register/tZwsc–hrj8pEtDgSBP6rxNyT50_di53DdkF\nWHERE\nOnline\nProgram\nplease check the Program of the event\nFor more information, please check the official site of the event.\n_\nDon’t miss out our Upcoming events!\n
URL:https://cmc.deusto.eus/events-calendar/deds2024/
CATEGORIES:EZuazua,Seminar/Talk
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