Computer Systems Modeling and its connection to model-based Machine Learning

Authors

  • Edmundo de Souza e Silva Federal University of Rio de Janeiro

DOI:

https://doi.org/10.5753/compbr.2023.51.3996

Keywords:

Computer Systems Modeling and Analysis, Computational Models, Machine Learning

Abstract

Artificial Intelligence (AI) has drawn significant attention these days. This text aims to highlight the fundamental role of computational models in several areas of Computing, and how understanding what a model is, along with their supporting theory, provides the foundations for Machine Learning algorithms.

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References

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F. Baskett, K. Chandy, R. Muntz, and F. Palacios, “Open, Closed and Mixed Networks of Queues with Different Classes of Customers,” Journal of the ACM, vol. 22, pp. 248–260, 1975.

L. Kleinrock, Queueing Systems, Volume II: Computer Applications. Wiley-Interscience, 1976.

E. de Souza e Silva and H. R. Gail, “Calculating availability and performability measures of repairable computer systems using randomization,” J. ACM, vol. 36, no. 1, pp. 171–193, 1989.

E. de Souza e Silva, R. M. M. Leão, and R. R. Muntz, “Performance Evaluation with Hidden Markov Models,” ser. Lecture Notes in Computer Science, vol. 6821. Springer, 2010, pp. 112–128.

K. P. Murphy, Probabilistic Machine Learning: An Introduction. MIT Press, 2022.

T. M. Mitchell, “Machine Learning”, McGraw-Hill Science, 1997.

Baseada na definição de Arthur Samuel (1959) Disponível em: [link].

Published

2023-12-28

How to Cite

Silva, E. de S. e. (2023). Computer Systems Modeling and its connection to model-based Machine Learning. Brazil Computing, (51), 55–60. https://doi.org/10.5753/compbr.2023.51.3996

Issue

Section

Papers