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SUMMARY:Harbir Antil (George Mason University\, Fairfex\, VA 22030\, USA)
DTSTART:20200922T130000Z
DTEND:20200922T140000Z
DTSTAMP:20260422T225703Z
UID:RCMaths/1
DESCRIPTION:Title: <a href="https://researchseminars.org/talk/RCMaths/1/">
 Optimal Control and Deep Learning with Fractional Operators</a>\nby Harbir
  Antil (George Mason University\, Fairfex\, VA 22030\, USA) as part of AIM
 S-Cameroon Research Center Colloquium Series\n\n\nAbstract\nFractional cal
 culus and its application to anomalous diffusion has recently received a t
 remendous amount of attention. In complex/heterogeneous material mediums\,
  the long-range correlations or hereditary material properties are presume
 d to be the cause of such anomalous behavior. Owing to the revival of frac
 tional calculus\, these effects are now conveniently modeled by fractional
 -order differential operators and the governing equations are reformulated
  accordingly. Similarly\, the potential of fractional operators has been h
 arnessed in various scientific domains like geophysical electromagnetics\,
  imaging science\, deep learning\, etc.\n\nIn this talk\, fractional opera
 tors will be introduced and both linear and nonlinear\, fractional-order d
 ifferential equations will be discussed. New notions of optimal control an
 d optimization under uncertainty will be presented. A special emphasis wil
 l be given on enriching Deep Neural Networks using fractional operators. S
 everal applications from geophysics\, imaging science\, and deep learning 
 will be presented.\n
LOCATION:https://researchseminars.org/talk/RCMaths/1/
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