Now showing items 1-7 of 7

    • An eager regression method based on best feature projections 

      Aydın, Tolga; Güvenir, H. Altay (Springer, Berlin, Heidelberg, 2001)
      This paper describes a machine learning method, called Regression by Selecting Best Feature Projections (RSBFP). In the training phase, RSBFP projects the training data on each feature dimension and aims to find the ...
    • Guest editor’s introduction 

      Akman, V. (Springer, 1998)
    • Learning problem solving strategies using refinement and macro generation 

      Güvenir, H. A.; Ernst, G. W. (Elsevier BV, 1990)
      In this paper we propose a technique for learning efficient strategies for solving a certain class of problems. The method, RWM, makes use of two separate methods, namely, refinement and macro generation. The former is a ...
    • A re-examination of computational creativity through non-human animals 

      Ahmed, Nashiha (Bilkent University, 2020-06)
      The advancement of artificial intelligence suggests signs of computational creativity; however, the case for computational creativity is undermined by an anthropocentric bias. In this thesis, I attempt to broaden the ...
    • Situated nonmonotonic temporal reasoning with BABY-SIT 

      Tın, E.; Akman, V. (IOS Press, 1997)
      After a review of situation theory and previous attempts at 'computational' situation theory, we present a new programming environment, BABY-SIT, which is based on situation theory. We then demonstrate how problems requiring ...
    • Turing test: 50 years later 

      Saygin, A. P.; Cicekli, I.; Akman, V. (Springer, 2000)
      The Turing Test is one of the most disputed topics in artificial intelligence, philosophy of mind, and cognitive science. This paper is a review of the past 50 years of the Turing Test. Philosophical debates, practical ...
    • Two learning approaches for protein name extraction 

      Tatar, S.; Cicekli, I. (Academic Press, 2009)
      Protein name extraction, one of the basic tasks in automatic extraction of information from biological texts, remains challenging. In this paper, we explore the use of two different machine learning techniques and present ...