Browsing by Author "Durrant, Robert J."

Now showing items 1-5 of 13

  • Dimension-adaptive bounds on compressive FLD Classification

    Kabán, Ata; Durrant, Robert J. (Springer Berlin Heidelberg, 2013)
    Efficient dimensionality reduction by random projections (RP) gains popularity, hence the learning guarantees achievable in RP spaces are of great interest. In finite dimensional setting, it has been shown for the compressive ...
  • A diversity-aware model for majority vote ensemble accuracy

    Lim, Nick Jin Sean; Durrant, Robert J. (Addison-Wesley, 2020)
    Ensemble classifiers are a successful and popular approach for classification, and are frequently found to have better generalization performance than single models in practice. Although it is widely recognized that ...
  • Foreword: Special issue for the Journal Track of the 8th Asian Conference on Machine Learning (ACML 2016)

    Durrant, Robert J.; Kim, Kee-Eung; Holmes, Geoffrey; Marsland, Stephen; Sugiyama, Masashi; Zhou, Zhi-Hua (Springer, 2017)
    We, the guest editors, welcome you to this special issue of Machine Learning comprising papers accepted to the journal track of the 8th Asian conference on machine learning (ACML 2016), held at the University of Waikato, ...
  • How effective is Cauchy-EDA in high dimensions?

    Sanyang, Momodou L.; Durrant, Robert J.; Kabán, Ata (IEEE, 2016)
    We consider the problem of high dimensional blackbox optimisation via Estimation of Distribution Algorithms (EDA) and the use of heavy-tailed search distributions in this setting. Some authors have suggested that employing ...
  • Linear dimensionality reduction in linear time: Johnson-Lindenstrauss-type guarantees for random subspace

    Lim, Nick Jin Sean; Durrant, Robert J. (2017)
    We consider the problem of efficient randomized dimensionality reduction with norm-preservation guarantees. Specifically we prove data-dependent Johnson-Lindenstrauss-type geometry preservation guarantees for Ho's random ...

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  • Selected data exploration methods in hydroclimatology

    Vetrova, Varvara (University of Waikato, 2016)
    The volumes of climatological data are rapidly growing due to development of new acquisition platforms and advances in data storage technologies. Such advances provide new challenging problems for data analysis methods. ...