Now showing items 1-4 of 4

    • Clustered linear regression 

      Ari, B.; Güvenir, H. A. (Elsevier, 2002)
      Clustered linear regression (CLR) is a new machine learning algorithm that improves the accuracy of classical linear regression by partitioning training space into subspaces. CLR makes some assumptions about the domain and ...
    • Concept representation with overlapping feature intervals 

      Güvenir, H. A.; Koç, H. G. (Taylor & Francis Inc., 1998)
      This article presents a new form of exemplar-based learning method, based on overlapping feature intervals. In this model, a concept is represented by a collection of overlappling intervals for each feature and class. ...
    • A Deterministic Analysis of an Online Convex Mixture of Expert Algorithms 

      Ozkan, H.; Donmez, M. A.; Tunc, S.; Kozat, S. S. (IEEE, 2014-07)
      We analyze an online learning algorithm that adaptively combines outputs of two constituent algorithms (or the experts) running in parallel to model an unknown desired signal. This online learning algorithm is shown to ...
    • A fast neural-network algorithm for VLSI cell placement 

      Aykanat, C.; Bultan, T.; Haritaoğlu, İ. (Pergamon Press, 1998)
      Cell placement is an important phase of current VLSI circuit design styles such as standard cell, gate array, and Field Programmable Gate Array (FPGA). Although nondeterministic algorithms such as Simulated Annealing (SA) ...