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X-WR-CALNAME:CIGMO Seminar Series - Ioannis P. A. Papadopoulos
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CREATED:20260924T210352Z
DTEND;TZID=America/New_York:20261005T120000
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UID:706fe9qm5odrda2jtn48erdt9u@google.com
DTSTART;TZID=America/New_York:20261005T110000
LAST-MODIFIED:20260925T021128Z
DTSTAMP:20260925T021216Z
SUMMARY:CIGMO Seminar Series - Ioannis P. A. Papadopoulos
SEQUENCE:0
DESCRIPTION:Speaker: Ioannis P. A. Papadopoulos\nTitle: Mesh-dependent i
 teration count growth in primal-dual active set strategies\n\nAbstract: 
 Quadratic programming problems often arise in mathematical models\, and 
 primal-dual active set (PDAS) strategies provide a highly effective algo
 rithm for their solution. For finite-dimensional problems\, an equivalen
 ce between PDAS and semismooth Newton methods was established in 2002\, 
 explaining the fast local superlinear convergence observed for these met
 hods. This connection has also been shown to hold for certain infinite-d
 imensional problems\, such as optimal control problems with control cons
 traints.\n\nOn the other hand\, PDAS is not a semismooth Newton method w
 hen applied to the infinite-dimensional obstacle problem. It is neverthe
 less a semismooth Newton method for any finite-dimensional discretizatio
 n\, and local superlinear convergence is therefore observed in practice.
  But there is a catch: with each uniform refinement of the mesh\, the nu
 mber of iterations required for convergence grows dramatically\, eventua
 lly doubling with each refinement.\n\nThis phenomenon has been occasiona
 lly noted in the literature but never fully investigated. In this talk\,
  we provide a detailed explanation of why this mesh-dependent behaviour 
 occurs. We also investigate PDAS applied to the Signorini problem\, wher
 e the convergence behaviour is also mesh-dependent but fundamentally dif
 ferent from that of the obstacle problem.\n\nPreprint: https://arxiv.org
 /abs/2607.26622.\n\n-::~:~::~:~:~:~:~:~:~:~:~:~:~:~:~:~:~:~:~:~:~:~:~:~:
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