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Statistics, Machine Learning, and Data Science: A Historical Review and a Look to the Future
Conference on Research, Innovation and Vision for the Future in Computing & Communication Technologies, 2023We are witnessing the beginning of a data driven era with the explosion of data, impact of data on our everyday lives, and advances of data processing methodology and technology. At this juncture, data science has emerged as an interdisciplinary field to
Tru Cao
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The Matérn Model: A Journey Through Statistics, Numerical Analysis and Machine Learning
Statistical Science, 2023The Mat\'ern model has been a cornerstone of spatial statistics for more than half a century. More recently, the Mat\'ern model has been central to disciplines as diverse as numerical analysis, approximation theory, computational statistics, machine ...
E. Porcu +3 more
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Machine Learning and Statistics in Clinical Research Articles-Moving Past the False Dichotomy.
JAMA pediatrics, 2023This Viewpoint describes the false dichotomy between statistics and machine learning and suggests considerations in building and evaluating clinical prediction models.
S. G. Finlayson, A. Beam, M. van Smeden
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Statistics meets Machine Learning
Oberwolfach Reports, 2021Theory and application go hand in hand in most areas of statistics. In a world flooded with huge amounts of data waiting to be analyzed, classified and transformed into useful outputs, the designing of fast, robust and stable algorithms has never been as important as it is today. On the other hand, irrespective of whether the focus is put on estimation,
Fadoua Balabdaoui +3 more
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Earthquake engineering & structural dynamics (Print), 2021
Evaluating the response statistics of nonlinear structures constitutes a key issue in engineering design. Hereby, the Monte Carlo method has proven useful, although the computational cost turns out to be considerably high.
Denny Thaler +3 more
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Evaluating the response statistics of nonlinear structures constitutes a key issue in engineering design. Hereby, the Monte Carlo method has proven useful, although the computational cost turns out to be considerably high.
Denny Thaler +3 more
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Machine learning versus statistical modeling
Biometrical Journal, 2014This is a discussion of the following papers: “Probability estimation with machine learning methods for dichotomous and multicategory outcome: Theory” by Jochen Kruppa, Yufeng Liu, Gérard Biau, Michael Kohler, Inke R. König, James D. Malley, and Andreas Ziegler; and “Probability estimation with machine learning methods for dichotomous and multicategory
Boulesteix, Anne-Laure, Schmid, Matthias
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Statistics, Data Mining, and Machine Learning in Astronomy
, 2019Statistics, Data Mining, and Machine Learning in Astronomy is the essential introduction to the statistical methods needed to analyze complex data sets from astronomical surveys such as the Panoramic Survey Telescope and Rapid Response System, the Dark ...
Ž. Ivezić +3 more
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International journal of sports science & coaching, 2020
The purpose of this research was to determine the on-field playing positions of a group of football players based on their technical-tactical behaviour using machine learning algorithms.
Abraham García-Aliaga +4 more
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The purpose of this research was to determine the on-field playing positions of a group of football players based on their technical-tactical behaviour using machine learning algorithms.
Abraham García-Aliaga +4 more
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Statistics, machine learning and deep learning for population genetic inference
, 2021Xinghu Qin
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