Now showing items 1-4 of 4

    • Asymptotically optimal contextual bandit algorithm using hierarchical structures 

      Neyshabouri, Mohammadreza Mohaghegh; Gökçesu, Kaan; Gökçesu, Hakan; Özkan, Hüseyin; Kozat, Süleyman Serdar (Institute of Electrical and Electronics Engineers, 2018)
      We propose an online algorithm for sequential learning in the contextual multiarmed bandit setting. Our approach is to partition the context space and, then, optimally combine all of the possible mappings between the ...
    • Competitive and online piecewise linear classification 

      Özkan, Hüseyin; Donmez, M.A.; Pelvan O.S.; Akman, A.; Kozat, Süleyman S. (IEEE, 2013)
      In this paper, we study the binary classification problem in machine learning and introduce a novel classification algorithm based on the 'Context Tree Weighting Method'. The introduced algorithm incrementally learns a ...
    • Online adaptive hierarchical space partitioning classifier 

      Kılıç, O. Fatih; Vanlı, N. D.; Özkan, Hüseyin; Delibalta, İ.; Kozat, Süleyman Serdar (IEEE, 2016)
      We introduce an on-line classification algorithm based on the hierarchical partitioning of the feature space which provides a powerful performance under the defined empirical loss. The algorithm adaptively partitions the ...
    • Online learning under adverse settings 

      Özkan, Hüseyin (Bilkent University, 2015-05)
      We present novel solutions for contemporary real life applications that generate data at unforeseen rates in unpredictable forms including non-stationarity, corruptions, missing/mixed attributes and high dimensionality. ...