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Browsing by Author "Assylbekov, Zhenisbek"

Browsing by Author "Assylbekov, Zhenisbek"

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  • A free/open-source hybrid morphological disambiguation tool for Kazakh 
    Assylbekov, Zhenisbek; Washington, Jonathan; Tyers, Francis; Nurkas, Assulan; Sundetova, Aida; Karibayeva, Aidana; Abduali, Balzhan; Amirova, Dina (DOI: 10.13140/RG.2.2.12467.43045, 2016-04)
    This paper presents the results of developing a morphological disambiguation tool for Kazakh. Starting with a previously developed rule-based approach, we tried to cope with the complex morphology of Kazakh by breaking ...
  • Convergence Rate of Fourier Neural Networks 
    Zhumekenov, Abylay (Nazarbayev University School of Science and Technology, 2019-04-26)
    The paper investigates a convergence rate for 2-layer feedforward Fourier Neural Network (FNN). Such networks are motivated by the approximation properties of wellknown Fourier series. Several implementations of FNNs ...
  • Copula functions in Credit Metrics’ VaR estimation 
    Magzanov, Shynggys (Nazarbayev University School of Science and Technology, 2019-08-08)
    Credit risk modelling of a portfolio of exposures is essential part of activity of every financial institution. However this procedure is complicated since the joint behavior of chosen exposures must be known. In this paper ...
  • Experiments with Russian to Kazakh sentence alignment 
    Assylbekov, Zhenisbek; Myrzakhmetov, Bagdat; Makazhanov, Aibek (The 4-th International Conference on Computer Processing of Turkic Languages “TurkLang 2016”, 2016)
    Sentence alignment is the final step in building parallel corpora, which arguably has the greatest impact on the quality of a resulting corpus and the accuracy of machine translation systems that use it for training. ...
  • Explorations on chaotic behaviors of Recurrent Neural Networks 
    Myrzakhmetov, Bagdat (Nazarbayev University School of Science and Technology, 2019-04-29)
    In this thesis work we analyzed the dynamics of the Recurrent Neural Network architectures. We explored the chaotic nature of state-of-the-art Recurrent Neural Networks: Vanilla Recurrent Network, Recurrent Highway ...