Now showing items 1-6 of 6

    • 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 ...
    • An efficient bandit algorithm for general weight assignments 

      Gökçesu, Kaan; Ergen, Tolga; Çiftçi, S.; Kozat, Süleyman Serdar (IEEE, 2017)
      In this paper, we study the adversarial multi armed bandit problem and present a generally implementable efficient bandit arm selection structure. Since we do not have any statistical assumptions on the bandit arm losses, ...
    • Estimating distributions varying in time in a universal manner 

      Gökçesu, Kaan; Manış, Eren; Kurt, Ali Emirhan; Yar, Ersin (IEEE, 2017)
      We investigate the estimation of distributions with time-varying parameters. We introduce an algorithm that achieves the optimal negative likelihood performance against the true probability distribution. We achieve this ...
    • Novelty detection using soft partitioning and hierarchical models 

      Ergen, Tolga; Gökçesu, Kaan; Şimşek, Mustafa; Kozat, Süleyman Serdar (IEEE, 2017)
      In this paper, we study novelty detection problem and introduce an online algorithm. The algorithm sequentially receives an observation, generates a decision and then updates its parameters. In the first step, to model the ...
    • An online minimax optimal algorithm for adversarial multiarmed bandit problem 

      Gökçesu, Kaan; Kozat, Süleyman Serdar (Institute of Electrical and Electronics Engineers, 2018)
      We investigate the adversarial multiarmed bandit problem and introduce an online algorithm that asymptotically achieves the performance of the best switching bandit arm selection strategy. Our algorithms are truly online ...
    • Sequential outlier detection based on incremental decision trees 

      Gökçesu, Kaan; Neyshabouri, Mohammadreza Mohaghegh; Gökçesu, Hakan; Serdar, Süleyman (IEEE, 2019)
      We introduce an online outlier detection algorithm to detect outliers in a sequentially observed data stream. For this purpose, we use a two-stage filtering and hedging approach. In the first stage, we construct a multimodal ...