Browsing by Subject "Machine Learning"

Now showing items 1-8 of 8

  • Deep Learning without Poor Local Minima 

    Unknown author (2016-05-23)
    In this paper, we prove a conjecture published in 1989 and also partially address an open problem announced at the Conference on Learning Theory (COLT) 2015. For an expected loss function of a deep nonlinear neural network, ...

  • Discriminative Gaussian Process Latent Variable Model for Classification 

    Unknown author (2007-03-28)
    Supervised learning is difficult with high dimensional input spacesand very small training sets, but accurate classification may bepossible if the data lie on a low-dimensional manifold. GaussianProcess Latent Variable ...

  • Evaluation of Machine Learning Tools for Predicting Sand Production 

    NGWASHI, Ronald Afungchwi (2021-03-12)
    Data analytics has only recently picked the interest of the oil and gas industry as it has made data visualization much simpler, faster, and cost-effective. This is driven by the promising innovative techniques in developing ...

  • Evaluation of Machine Learning Tools for Predicting Sand Production 

    Ngwashi, Ronald Afungchwi (AUST, 2021-03-10)
    Data analytics has only recently picked the interest of the oil and gas industry as it has made data visualization much simpler, faster, and cost-effective. This is driven by the promising innovative techniques in developing ...

  • Machine Learning Techniques for Malaria Incidence and Tuberculosis Prediction 

    Odu, Nkiruka Bridget (AUST, 2021-07-02)
    This research proposes machine learning techniques to develop models that would facilitate decision-making in health informatics. It focuses on using efficient machine learning techniques to solve the pressing need in the ...

  • Object Detection in Images by Components 

    Unknown author (1999-08-11)
    In this paper we present a component based person detection system that is capable of detecting frontal, rear and near side views of people, and partially occluded persons in cluttered scenes. The framework that is ...

  • Probability of Wellbore Failure and its Prediction Using Machine Learning 

    Kolade, Emmanuel Bamidele (AUST, 2019-06-09)
    Wellbore instability (WI) is one of the major challenges experienced during drilling operations costing the oil and gas industry over $1 billion yearly. During the drilling, borehole breakout and drilling induced fractures ...

  • Towards Understanding Generalization via Analytical Learning Theory 

    Unknown author (2018-10-01)
    This paper introduces a novel measure-theoretic theory for machine learning that does not require statistical assumptions. Based on this theory, a new regularization method in deep learning is derived and shown to ...