Now showing items 1-7 of 7

    • Communication efficient channel estimation over distributed networks 

      Sayın, Muhammed O.; Vanlı, N. Denizcan; Göze, T.; Kozat, Süleyman Serdar (IEEE, 2014)
      We study diffusion based channel estimation in distributed architectures suitable for various communication applications such as cognitive radios. Although the demand for distributed processing is steadily growing, these ...
    • Comprehensive lower bounds on sequential prediction 

      Vanlı, N. Denizcan; Sayın, Muhammed O.; Ergüt, S.; Kozat, Süleyman S. (IEEE, 2014-09)
      We study the problem of sequential prediction of real-valued sequences under the squared error loss function. While refraining from any statistical and structural assumptions on the underlying sequence, we introduce a ...
    • Energy consumption forecasting via order preserving pattern matching 

      Vanlı, N. Denizcan; Sayın, Muhammed O.; Yıldız, Hikmet; Göze, Tolga; Kozat, Süleyman S. (IEEE, 2014-12)
      We study sequential prediction of energy consumption of actual users under a generic loss/utility function. Particularly, we try to determine whether the energy usage of the consumer will increase or decrease in the future, ...
    • Improved convergence performance of adaptive algorithms through logarithmic cost 

      Sayın, Muhammed O.; Vanlı, N. Denizcan; Kozat, Süleyman S. (IEEE, 2014-05)
      We present a novel family of adaptive filtering algorithms based on a relative logarithmic cost. The new family intrinsically combines the higher and lower order measures of the error into a single continuous update based ...
    • 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 ...
    • 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 ...
    • 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 ...