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      MLSysOps: Machine Learning for Autonomic System Operation in the Heterogeneous Edge-Cloud Continuum

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      Spyros LalisSpyros Lalis, Professor
      E-mail: lalis@e-ce.uth.gr

      TitleMLSysOps: Machine Learning for Autonomic System Operation in the Heterogeneous Edge-Cloud Continuum
      Duration2023 – 2025
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ECE452 Special Topics in Applied Mathematics

Home » Studies » Undergraduate Studies » Undergraduate Courses » ECE452 Special Topics in Applied Mathematics
Subject AreaApplications and Foundations of Computer Science
SemesterSemester 8 – Spring
TypeElective
Teaching Hours4
ECTS6
Course Sitehttps://eclass.uth.gr/courses/E-CE_U_283/
Course Director

Emmanouil VavalisEmmanouil Vavalis, Professor
E-mail: mav@e-ce.uth.gr

Course Instructor
  • Emmanouil Vavalis, Professor
    E-mail: mav@e-ce.uth.gr
  • Description
  • Learning Outcomes

Introductory Review of Matrix Theory. (Linear Vector Spaces, Square Matrices, Eigenvalues and Eigenvectors, Norms.) Direct Methods of Solution of Linear Systems, GaussElimination Method and itsModifications, LU Factorization, Method ofCholesky, Elements of Perturbation Theory, Iterative Improvement of Numerical Solution of Linear Systems. Iterative Methods of Solution of Linear Systems, Classical Iterative Methods,General Iterative Method, Methods of Jacobi and Gauss-Seidel, Convergence Acceleration Techniques (Extrapolation), SOR Method, Symmetric SOR (SSOR) Method, Applications (Difference Equations, Tensor Products). Minimization Methods for the Solution of Linear Systems (Methods of Steepest Descent, Conjugate Directions,Conjugate Gradient (CG), Preconditioned CG). Least Squares Method, Theory of Linear Problem, Gram-Schmidt Method, QR Analysis, Householder and Givens Transformations, Analysis of Singular Values (SVD). Numerical Methods for the Determination of the Eigenvalues and Eigenvectors, Power Method and its Variations, Determination of other Eigenvalues.

Students will be able to

  • Understand the basic concepts of Numerical Linear Algebra (E.g., Solution of linear systems of algebraic equations by using direct and iterative methods).
  • Solve practical problems as those that are produced after the discretization Partial Differential Equations.
  • Analyze the accuracy of the obtained solutions as well as the convergence and the stability of the algorithms that are used.
  • Compare similar algorithms and select the one that is most appropriate for the characteristics of the particular problem considered

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Contact Info

  • Sekeri – Cheiden Str, Pedion Areos, Volos
  • +30 24210 74967
  • +30 24210 74934
  • Email: gece@e-ce.uth.gr

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