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SUMMARY:Contraction and Convexity\, Robustness and Regularisation - Prof. 
 Ian Manchester\, University of Sydney
DTSTART:20211209T090000Z
DTEND:20211209T100000Z
UID:TALK165562@talks.cam.ac.uk
CONTACT:Thiago Burghi
DESCRIPTION:Understanding the interplay of dynamics\, data\, and optimizat
 ion is a central focus of many fields including control theory and machine
  learning. Contracting dynamical systems and convex optimization problems 
 are closely-related notions of “nice” or “well-behaved” settings\,
  in which the main advantages of the linear setting carry over more or les
 s intact. Contraction and convexity are both also closely linked to the th
 eory of monotone operators\, which has recently found application in new m
 achine learning models known as “equilibrium networks”. Meanwhile\, co
 mputational methods to quantify “robustness” of dynamical systems can 
 be fruitfully applied as “regularisation” to improve generalisation of
  models fit to data. In this talk\, we will explore these links at an intr
 oductory level and also through a selection of recent results in nonlinear
  control design\, observer design\, system identification\, and machine le
 arning.\n\nSpeaker biography:\nIan R. Manchester received the B.E. (Hons 1
 ) and Ph.D. degrees in electrical engineering from the University of New S
 outh Wales\, Sydney\, NSW\, Australia\, in 2002 and 2006\, respectively. H
 e held postdoctoral research positions with Umeå University\, Sweden\, an
 d the Massachusetts Institute of Technology (MIT). Since 2012\, he has bee
 n with The University of Sydney\, Australia\, where he is currently  Profe
 ssor of Mechatronic Engineering\, Director of the Australian Centre for fi
 eld Robotics\, and Co-Director of the Sydney Institute for Robotics and In
 telligent Systems. His research interests include algorithms for control\,
  learning\, and identification of nonlinear dynamical systems\, with appli
 cations in robotics and biomedical engineering. He is an Associate Editor 
 for the IEEE Robotics and Automation Letters.
LOCATION:Dyson Seminar Room\, Department of Engineering / Online (Zoom)
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