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SUMMARY:Harbir Antil (George Mason University\, Fairfex\, VA 22030\, USA)
DTSTART:20200922T130000Z
DTEND:20200922T140000Z
DTSTAMP:20260404T110831Z
UID:RCMaths/1
DESCRIPTION:Title: <a href="https://stable.researchseminars.org/talk/RCMat
 hs/1/">Optimal Control and Deep Learning with Fractional Operators</a>\nby
  Harbir Antil (George Mason University\, Fairfex\, VA 22030\, USA) as part
  of AIMS-Cameroon Research Center Colloquium Series\n\n\nAbstract\nFractio
 nal calculus and its application to anomalous diffusion has recently recei
 ved a tremendous amount of attention. In complex/heterogeneous material me
 diums\, the long-range correlations or hereditary material properties are 
 presumed to be the cause of such anomalous behavior. Owing to the revival 
 of fractional calculus\, these effects are now conveniently modeled by fra
 ctional-order differential operators and the governing equations are refor
 mulated accordingly. Similarly\, the potential of fractional operators has
  been harnessed in various scientific domains like geophysical electromagn
 etics\, imaging science\, deep learning\, etc.\n\nIn this talk\, fractiona
 l operators will be introduced and both linear and nonlinear\, fractional-
 order differential equations will be discussed. New notions of optimal con
 trol and optimization under uncertainty will be presented. A special empha
 sis will be given on enriching Deep Neural Networks using fractional opera
 tors. Several applications from geophysics\, imaging science\, and deep le
 arning will be presented.\n
LOCATION:https://stable.researchseminars.org/talk/RCMaths/1/
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