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Parameter Identifiability in Statistical Machine Learning: A Review
Neural Computation, 2017This review examines the relevance of parameter identifiability for statistical models used in machine learning. In addition to defining main concepts, we address several issues of identifiability closely related to machine learning, showing the advantages and disadvantages of state-of-the-art research and demonstrating recent progress.
Zhi-Yong Ran, Bao-Gang Hu
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Statistical Machine Learning and Computational Biology
2007 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2007), 2007Statistical machine learning is a field that combines algorithmic ideas with foundational concepts from probability and statistics. This combination makes statistical machine learning an essential tool for computational biology, in part because probabilistic notions are inherent in biology (arising, e.g., via thermodynamics, recombination and germline ...
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Statistics (Berlin)
The rapid development of artificial intelligence applications based on machine learning is creating not only many opportunities but also risks. The recent regulatory and political debate, at the international level, emphasizes the urgent need to develop ...
Paolo Giudici
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The rapid development of artificial intelligence applications based on machine learning is creating not only many opportunities but also risks. The recent regulatory and political debate, at the international level, emphasizes the urgent need to develop ...
Paolo Giudici
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2019
AbstractThis chapter describes in detail how the main techniques of statistical machine learning can be constructed from the components described in earlier chapters. It presents these concepts in a way which demonstrates how these techniques can be viewed as special cases of a more general probabilistic model which we fit to some data.
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AbstractThis chapter describes in detail how the main techniques of statistical machine learning can be constructed from the components described in earlier chapters. It presents these concepts in a way which demonstrates how these techniques can be viewed as special cases of a more general probabilistic model which we fit to some data.
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Science of the Total Environment, 2019
The present study is carried out in the context of the continuous increase, worldwide, of the number of flash-floods phenomena. Also, there is an evident increase of the size of the damages caused by these hazards.
R. Costache, Haoyuan Hong, Q. Pham
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The present study is carried out in the context of the continuous increase, worldwide, of the number of flash-floods phenomena. Also, there is an evident increase of the size of the damages caused by these hazards.
R. Costache, Haoyuan Hong, Q. Pham
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Machine and Statistical Learning
2017Databases and big data are used for constructing models to have a better understanding of the data, or to make decisions. Machine and statistical learning offer tools for this purpose. In this chapter we review some of the methods in these areas that are of relevance in this book.
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Is K-fold cross validation the best model selection method for Machine Learning?
Information FusionAs a technique that can compactly represent complex patterns, machine learning has significant potential for predictive inference. K-fold cross-validation (CV) is the most common approach to ascertaining the likelihood that a machine learning outcome is ...
J. Górriz +4 more
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Reliability in Machine Learning
Philosophy CompassIssues of reliability are claiming center‐stage in the epistemology of machine learning. This paper unifies different branches in the literature and points to promising research directions, whilst also providing an accessible introduction to key concepts
Thomas Grote +2 more
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Survey of Computerized Adaptive Testing: A Machine Learning Perspective
IEEE Transactions on Pattern Analysis and Machine IntelligenceComputerized Adaptive Testing (CAT) offers an efficient and personalized method for assessing examinee proficiency by dynamically adjusting test questions based on individual performance.
Qi Liu +14 more
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