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CATEGORIES:CUED Control Group Seminars
SUMMARY:Exploiting Sparsity in Semidefinite and Sum of Squ
ares Programming - Antonis Papachristodoulou\, Uni
versity of Oxford
DTSTART;TZID=Europe/London:20200220T140000
DTEND;TZID=Europe/London:20200220T150000
UID:TALK132418AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/132418
DESCRIPTION:Semidefinite and sum of squares optimization have
found a wide range of applications\, including con
trol theory\, fluid dynamics\, machine learning\,
and power systems. In theory they can be solved in
polynomial time using interior-point methods. How
ever\, these methods are only practical for small-
to medium- sized problem instances.\n\nFor large
instances\, it is essential to exploit or even imp
ose sparsity and structure within the problem in o
rder to solve the associated programs efficiently.
In this talk I will present recent results on the
analysis and design of networked systems\, where
chordal sparsity can be used to decompose the resu
lting SDPs\, and solve an equivalent set of smalle
r semidefinite constraints. I will also discuss ho
w sparsity and operator-splitting methods can be u
sed to speed up computation of large SDPs and intr
oduce our open-source solver CDCS. Lastly\, I will
extend the decomposition result on SDPs to SOS op
timization with polynomial constraints\, revealing
a practical way to connect SOS optimization and D
SOS/SDSOS optimization for sparse problem instance
s.\n
LOCATION:Cambridge University Engineering Department\, Semi
nar Room JDB
CONTACT:Alberto Padoan
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