Machine Learning Integration in Computational System Design

Authors

  • Riley Hernandez PhD
  • Dana Robinson PhD
  • Pat Carter PhD

Keywords:

machine learning, system design, algorithm integration, performance enhancement, user experience

Abstract

This article explores the integration of machine learning techniques in the design of computational systems. It highlights the benefits of machine learning in improving system performance, adaptability, and efficiency. The paper discusses various models and algorithms that can be incorporated into system design to enhance functionality and user experience.
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Author Biographies

Riley Hernandez, PhD

PhD
Politecnico di Milano
Piazza Leonardo da Vinci, 32, 20133 Milano MI, Italy

Dana Robinson, PhD

PhD
KTH Royal Institute of Technology
Brinellvägen 8, 114 28 Stockholm, Sweden

Pat Carter, PhD

PhD
National University of Singapore
21 Lower Kent Ridge Rd, Singapore 119077

References

KUMAR, Nitin; KATARIA, Vipin. Enhanced Sentiment Classification using a Multi-layered Stacked Ensemble Architecture.

Рагимов, Э. Р. (2006). Об одном подходе оценки риска при проектировании защищенных корпоративных сетей. Информационные технологии моделирования и управления, (1), 94-98.

Published

2024-09-25

Issue

Section

Articles