Now showing items 1-8 of 8

    • Bağlam ağaçları ile ardışık doğrusal olmayan bağlanım 

      Vanlı, N. Denizcan; Kozat, Süleyman S. (IEEE, 2014-04)
      Bu bildiride, ardışık doğrusal olmayan bağlanım problemi incelenmiş ve bağlam ağaçları kullanarak etkili bir öğrenme algoritması sunulmuştur. Bu amaçla, bağlanım alanı parçalara ayrılmış ve oluşan bölgeler bağlam ağacı ile ...
    • A comprehensive approach to universal piecewise nonlinear regression based on trees 

      Vanli, N. D.; Kozat, S. S. (IEEE, 2014)
      In this paper, we investigate adaptive nonlinear regression and introduce tree based piecewise linear regression algorithms that are highly efficient and provide significantly improved performance with guaranteed upper ...
    • 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 ...
    • Highly efficient nonlinear regression for big data with lexicographical splitting 

      Neyshabouri, M. M.; Demir, O.; Delibalta, I.; Kozat, S. S. (Springer London, 2017)
      This paper considers the problem of online piecewise linear regression for big data applications. We introduce an algorithm, which sequentially achieves the performance of the best piecewise linear (affine) model with ...
    • Nonlinear regression using second order methods 

      Civek, Burak Cevat; Delibalta, İ.; Kozat, Süleyman Serdar (IEEE, 2016)
      We present a highly efficient algorithm for the online nonlinear regression problem. We process only the currently available data and do not reuse it, hence, there is no need for storage. For the nonlinear regression, we ...
    • Online distributed nonlinear regression via neural networks 

      Ergen, Tolga; Kozat, Süleyman Serdar (IEEE, 2017)
      In this paper, we study the nonlinear regression problem in a network of nodes and introduce long short term memory (LSTM) based algorithms. In order to learn the parameters of the LSTM architecture in an online manner, ...
    • 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 ...
    • Variable selection in regression using maximal correlation and distance correlation 

      Yenigün, C. D.; Rizzo, M. L. (Taylor and Francis Ltd., 2015)
      In most of the regression problems the first task is to select the most influential predictors explaining the response, and removing the others from the model. These problems are usually referred to as the variable selection ...