BEGIN:VCALENDAR
VERSION:2.0
PRODID:icalendar-ruby
CALSCALE:GREGORIAN
X-WR-CALNAME:Probability and Statistics Seminar: Kernel ordinary differenti
 al equations
X-WR-TIMEZONE:Pacific Time (US & Canada)
BEGIN:VEVENT
DTSTAMP:20260820T002009Z
UID:tag:localist.com\,2008:EventInstance_45889614677582
DTSTART:20240322T223000Z
DTEND:20240322T233000Z
DESCRIPTION:Xiaowu Dai\, UCLA\n\n\nTitle: Kernel ordinary differential equa
 tions\n\n\nAbstract: The ordinary differential equation (ODE) is widely us
 ed in modelling biological and physical processes in science. A new reprod
 ucing kernelbased approach is proposed for the estimation and inference of
  ODE given noisy observations. The functional forms in ODE are not assumed
  to be known or restricted to be linear or additive\, and pairwise interac
 tions are allowed. Sparse estimation is performed to select individual fun
 ctionals and construct confidence intervals for the estimated signal traje
 ctories. The estimation optimality and selection consistency of kernel ODE
  are established under both the low-dimensional and high-dimensional setti
 ngs\, where the number of unknown functionals can be smaller or larger tha
 n the sample size. The proposal tackles several important problems that ar
 e not yet fully addressed in smoothing spline analysis of variance (SS-ANO
 VA) framework\, and extends the existing methods of dynamic causal modelin
 g.
GEO:34.022409;-118.291027
LOCATION:Kaprielian Hall (KAP)\, 414
SUMMARY:Probability and Statistics Seminar: Kernel ordinary differential eq
 uations
URL;VALUE=URI:https://calendar.usc.edu/event/probability-and-statistics-sem
 inar-kernel-ordinary-differential-equations
CATEGORIES:Lecture / Talk / Workshop
END:VEVENT
END:VCALENDAR