• Upcoming Events
  • Awards
  • Distinguished Lecture
  • Latest Seminars and Events
  • Others
  • Seminars
  • Workshop and Conference
  • Past Events
  • Student Issue
Upcoming Events
Topic:Low-Rank Covariance Function Estimation for Multidimensional Functional Data
Time:2:00 pm - 3:00 pm
Venue:Y C Liang Hall (LHC) 106
Speaker:Professor Raymond Wong


Multidimensional function data arise from many fields nowadays. The covariance function plays an important role in the analysis of such increasingly common data. In this talk, I will present a novel nonparametric covariance function estimation approach under the framework of reproducing kernel Hilbert spaces (RKHS) that can handle both sparse and dense functional data. We extend multilinear rank structures for (finite-dimensional) tensors to functions, which allow for flexible modeling of both covariance operators and marginal structures. The proposed framework can guarantee that the resulting estimator is automatically semi-positive definite, and can incorporate various spectral regularizations. The trace-norm regularization in particular can promote low ranks for both covariance operator and marginal structures. Despite the lack of a closed form, under mild assumptions, the proposed estimator can achieve unified theoretical results that hold for any relative magnitudes between the sample size and the number of observations per sample field, and the rate of convergence reveals the “phase-transition” phenomenon from sparse to dense functional data.

İstanbul escort bayan sivas escort samsun escortbayan sakarya escort Muğla escort Mersin escort Escort malatya Escort konya Kocaeli Escort Kayseri Escort izmir escort bayan hatay bayan escort antep Escort bayan eskişehir escort bayan erzurum escort bayan elazığ escort diyarbakır escort escort bayan Çanakkale Bursa Escort bayan Balıkesir escort aydın Escort Antalya Escort ankara bayan escort Adana Escort bayan