Recent Submissions

  • On the ubiquity of the Bayesian paradigm in statistical machine learning and data science 

    Fokoué, Ernest (Vysoké učení technické v Brně, Fakulta strojního inženýrství, Ústav matematiky, 2019)
    This paper seeks to provide a thorough account of the ubiquitous natureof the Bayesian paradigm in modern statistics, data science and artificial intelli-gence. Once maligned, on the one hand by those ...
  • What do Asian and non-Asian scriptures have in common? An applied statistical machine learning inquiry 

    Sah, Preeti; Fokoué, Ernest (Vysoké učení technické v Brně, Fakulta strojního inženýrství, Ústav matematiky, 2019)
    This paper presents a substantially detailed statistical machine learningapproach to the analysis of several aspects of sacred texts from both the Asian andBiblical scriptural canons. The corpus herein considered consists ...
  • Prediction and evaluation in College Hockey using the Bradley–Terry–Zermelo model 

    Whelan, John T.; Wodon, Adam (Vysoké učení technické v Brně, Fakulta strojního inženýrství, Ústav matematiky, 2019)
    We describe the application of the Bradley–Terry model to NCAA Divi-sion I Men’s Ice Hockey. A Bayesian construction gives a joint posterior probabilitydistribution for the log-strength parameters, given a set of game ...
  • Multi-stage fault warning for large electric grids using anomaly detection and machine learning 

    Raja, Sanjeev; Fokoué, Ernest (Vysoké učení technické v Brně, Fakulta strojního inženýrství, Ústav matematiky, 2019)
    In the monitoring of a complex electric grid, it is of paramount impor-tance to provide operators with early warnings of anomalies detected on the network,along with a precise classification and diagnosis of the specific ...
  • On a global measure of nonlinearity and its application in parameter estimation in nonlinear regression 

    Khinkis, Leonid (Vysoké učení technické v Brně, Fakulta strojního inženýrství, Ústav matematiky, 2019)
    The theoretical and computational challenges in least squares estimationof parameters in nonlinear regression models are well documented in statisticalliterature. The measures of nonlinearity are intended ...
  • On the versatility and polyvalence of certain statistical learning machines 

    Fokoué, Ernest (Vysoké učení technické v Brně, Fakulta strojního inženýrství, Ústav matematiky, 2019)
    As data science and its flurry of lucrative career opportunities continue to dominatestrategic planning meetings at companies and universities around the world, it isremarkable to notice that mathematics, the queen of all ...
  • An empirical demonstration of the no free lunch theorem 

    Ogundepo, Ezekiel Adebayo; Fokoué, Ernest (Vysoké učení technické v Brně, Fakulta strojního inženýrství, Ústav matematiky, 2019)
    In this paper, we provide a substantial empirical demonstration of thestatistical machine learning result known as the No Free Lunch Theorem (NFLT).We specifically compare the predictive performances of a wide ...