Now showing items 1-4 of 4

    • Logarithmic regret bound over diffusion based distributed estimation 

      Sayın, Muhammed O.; Vanlı, Nuri Denizcan; Kozat, Süleyman Serdar (IEEE, 2014)
      We provide a logarithmic upper-bound on the regret function of the diffusion implementation for the distributed estimation. For certain learning rates, the bound shows guaranteed performance convergence of the distributed ...
    • Online nonlinear modeling via self-organizing trees 

      Vanlı, Nuri Denizcan; Kozat, Süleyman Serdar (Elsevier, 2018)
      We study online supervised learning and introduce regression and classification algorithms based on self-organizing trees (SOTs), which adaptively partition the feature space into small regions and combine simple local ...
    • Sequential nonlinear learning 

      Vanlı, Nuri Denizcan (Bilkent University, 2015)
      We study sequential nonlinear learning in an individual sequence manner, where we provide results that are guaranteed to hold without any statistical assumptions. We address the convergence and undertraining issues of ...
    • Twice-universal piecewise linear regression via infinite depth context trees 

      Vanlı, Nuri Denizcan; Sayın, Muhammed O.; Göze, T.; Kozat, Süleyman Selim (IEEE, 2015)
      We investigate the problem of sequential piecewise linear regression from a competitive framework. For an arbitrary and unknown data length n, we first introduce a method to partition the regressor space. Particularly, we ...