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SUMMARY:Yiwen Chen (UBC-O hosted) (UBC Okanagan)
DTSTART:20240404T210000Z
DTEND:20240404T220000Z
DTSTAMP:20260513T185903Z
UID:SFUOR/32
DESCRIPTION:Title: <a href="https://researchseminars.org/talk/SFUOR/32/">Q
 -fully quadratic modeling and its application in a random subspace derivat
 ive-free method</a>\nby Yiwen Chen (UBC-O hosted) (UBC Okanagan) as part o
 f PIMS-CORDS SFU Operations Research Seminar\n\nLecture held in ASB 10908.
 \n\nAbstract\nDerivative-free optimization (DFO) methods are a class of op
 timization methods that do not use the derivatives of the objective or con
 straint functions.  Model-based DFO methods are an important class of DFO 
 methods that are known to struggle with solving high-dimensional optimizat
 ion problems.  Recent research has shown that incorporating random subspac
 es into model-based DFO methods has the potential to improve their perform
 ance on high-dimensional problems. However\, most of the current theoretic
 al and practical results are based on linear approximation models due to t
 he complexity of quadratic approximation models. In this talk\, we propose
  a random subspace derivative-free trust-region algorithm based on quadrat
 ic approximations. Unlike most of its precursors\, this algorithm does not
  require any special form of objective function. We study the geometry of 
 sample sets\, the error bounds for approximations\, and the quality of sub
 spaces. In particular\, we provide a technique to construct Q-fully quadra
 tic models\, which is easy to analyze and implement. We present an almost-
 sure global convergence result of our algorithm and give an upper bound on
  the expected number of iterations to find a sufficiently small gradient. 
 We also develop numerical experiments to compare the performance of our al
 gorithm using both linear and quadratic approximation models. The numerica
 l results demonstrate the strengths and weaknesses of using quadratic appr
 oximations.\n
LOCATION:https://researchseminars.org/talk/SFUOR/32/
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