Blar i Fakultet for teknologi, kunst og design (TKD) på tidsskrift "Applied intelligence (Boston)"

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    • Efficient quantile tracking using an oracle 

      Hammer, Hugo Lewi; Yazidi, Anis; Riegler, Michael; Rue, Håvard (Applied intelligence (Boston);, Peer reviewed; Journal article, 2022-04-14)
      Concept drift is a well-known issue that arises when working with data streams. In this paper, we present a procedure that allows a quantile tracking procedure to cope with concept drift. We suggest using expected quantile ...

    • A new quantile tracking algorithm using a generalized exponentially weighted average of observations 

      Hammer, Hugo Lewi; Yazidi, Anis; Rue, Håvard (Applied Intelligence;Published online 10 November, 2018, Journal article; Journal article; Peer reviewed, 2018-11-10)
      The Exponentially Weighted Average (EWA) of observations is known to be state-of-art estimator for tracking expectations of dynamically varying data stream distributions. However, how to devise an EWA estimator to rather ...

    • On solving the SPL problem using the concept of probability flux 

      Abolpour Mofrad, Asieh; Yazidi, Anis; Hammer, Hugo Lewi (Applied intelligence;Volume 49, Issue 7, July 2019, Journal article; Peer reviewed, 2019-02-02)
      The Stochastic Point Location (SPL) problem [20] is a fundamental learning problem that has recently found a lot of research attention. SPL can be summarized as searching for an unknown point in an interval under faulty ...

    • Parameter estimation in abruptly changing dynamic environments using stochastic learning weak estimator 

      Hammer, Hugo Lewi; Yazidi, Anis (Applied Intelligence;Volume 48, Issue 11, Journal article; Peer reviewed, 2018-05-25)
      Many real-life dynamical systems experience abrupt changes followed by almost stationary periods. In this paper, we consider streams of data exhibiting such abrupt behavior and investigate the problem of tracking their ...

    • Solving stochastic nonlinear resource allocation problems using continuous learning automata 

      Yazidi, Anis; Hammer, Hugo Lewi (Applied Intelligence;November 2018, Volume 48, Issue 11, Journal article; Peer reviewed, 2018-06-23)
      This paper deals with the Stochastic Non-linear Fractional Equality Knapsack (NFEK) problem which is a fundamental resource allocation problem based on incomplete and noisy information [7, 8]. The NFEK problem arises ...

    • Two-time scale learning automata: an efficient decision making mechanism for stochastic nonlinear resource allocation 

      Yazidi, Anis; Hammer, Hugo Lewi; Jonassen, Tore Møller (Applied Intelligence;Volume 49, Issue 9, Journal article; Peer reviewed, 2019-04-11)
      The Stochastic Non-linear Fractional Equality Knapsack (NFEK) problem is a substantial resource allocation problem which admits a large set of applications such as web polling under polling constraints, and constrained ...