BEGIN:VCALENDAR
PRODID:-//Ben Fortuna//iCal4j 1.0//EN
VERSION:2.0
CALSCALE:GREGORIAN
X-WR-CALNAME:Seminar\, Optimization and systems theory
BEGIN:VEVENT
DTSTAMP:20201202T195641Z
SUMMARY:Atte Aalto: Gene expression modelling from experimental data
LOCATION:KTH\, F11
DTSTART:20200131T100000Z
DTEND:20200131T110000Z
UID:abc7a289-34b3-4182-8862-4fe22aa579b2
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20201202T195641Z
SUMMARY:Elina RĂ¶nnberg: Decomposition approaches for a large-scale schedu
ling problem
LOCATION:Zoom\, meeting ID: 636 5838 1373
DTSTART:20201016T090000Z
DTEND:20201016T100000Z
UID:35a77670-84d4-4ee6-b202-1bb759044d71
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20201202T195641Z
SUMMARY:Anders Lansner: Theories\, models and simulations of human workin
g memory
LOCATION:Zoom meeting ID: 636 5838 1373
DTSTART:20201106T100000Z
DTEND:20201106T110000Z
UID:8db16836-ba0c-4092-86e0-61191be5d915
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20201202T195641Z
SUMMARY:Bernardo Pagnoncelli: Contextual chance-constrained programming
LOCATION:Zoom ID: 63658381373
DTSTART:20201113T100000Z
DTEND:20201113T110000Z
UID:15959b4e-bd65-474f-8cbf-5fed485b6237
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20201202T195641Z
SUMMARY:Approaches to accelerate methods for solving systems of equations
arising in nonlinear optimization
DESCRIPTION:In this pre-defense seminar\, I will present selected parts o
f my upcoming thesis. Methods for solving nonlinear optimization problem
s typically involve solving systems of equations. The thesis concerns ap
proaches for accelerating some of those methods. In our setting\, accele
rating involves finding a trade-off between the computational cost of an
iteration and the quality of the computed search direction. We have des
igned approaches for which theoretical results in ideal settings have be
en derived. We have also investigated the practical performance of the a
pproaches within and beyond the boundaries of the theoretical frameworks
with numerical simulations. \nThe initial part concerns solving strictl
y convex unconstrained quadratic optimization problems. In particular\,
exact linesearch limited-memory quasi-Newton methods which generate sear
ch directions parallel to those of the method of preconditioned conjugat
e gradients. The focus of the second part is approaches to accelerate pr
imal-dual interior-point methods. In particular\, approaches when the me
thod is applied to bound-constrained nonlinear optimization problems and
on quadratic optimization problems with linear inequality constraints.
LOCATION:Zoom Meeting ID: 636 5838 1373
DTSTART:20201211T100000Z
DTEND:20201211T110000Z
UID:e5fb4ba8-c60a-4821-82d5-6509ad955e24
END:VEVENT
END:VCALENDAR