Now showing items 1-4 of 4

    • Highly efficient hierarchical online nonlinear regression using second order methods 

      Civek, B. C.; Delibalta, I.; Kozat, S. S. (Elsevier B.V., 2017)
      We introduce highly efficient online nonlinear regression algorithms that are suitable for real life applications. We process the data in a truly online manner such that no storage is needed, i.e., the data is discarded ...
    • Piecewise linear regression based on adaptive tree structure using second order methods 

      Civek, Burak Cevat; Delibalta, İ.; Kozat, Süleyman Serdar (IEEE, 2016)
      We introduce a highly efficient online nonlinear regression algorithm. We process the data in a truly online manner such that no storage is needed, i.e., the data is discarded after used. For nonlinear modeling we use a ...
    • Piecewise nonlinear regression via decision adaptive trees 

      Vanlı, N. Denizcan; Sayın, Muhammed O.; Ergüt, S.; Kozat, Süleyman S. (IEEE, 2014-09)
      We investigate the problem of adaptive nonlinear regression and introduce tree based piecewise linear regression algorithms that are highly efficient and provide significantly improved performance with guaranteed upper ...
    • Sequential regression techniques with second order methods 

      Civek, Burak Cevat (Bilkent University, 2017-07)
      Sequential regression problem is one of the widely investigated topics in the machine learning and the signal processing literatures. In order to adequately model the underlying structure of the real life data sequences, ...