Unit NUMERICAL APPROXIMATION AND APPLICATIONS
- Course
- Mathematics
- Study-unit Code
- 55A00049
- Curriculum
- Matematica per l'economia e la finanza
- Teacher
- Bruno Iannazzo
- Teachers
-
- Bruno Iannazzo
- Hours
- 47 ore - Bruno Iannazzo
- CFU
- 6
- Course Regulation
- Coorte 2021
- Offered
- 2021/22
- Learning activities
- Affine/integrativa
- Area
- Attività formative affini o integrative
- Academic discipline
- MAT/08
- Type of study-unit
- Opzionale (Optional)
- Type of learning activities
- Attività formativa monodisciplinare
- Language of instruction
- English
- Contents
- Numerical methods for data science, machine learning and complex networks.
- Reference texts
- J. Nocedal, S. Wright, Numerical Optimization, Springer, 2006.
J. Demmel, Applied Numerical Linear Algebra, SIAM, 1996.
E. Estrada, The structure of complex networks, OUP, 2011. - Educational objectives
- Get into mathematical aspects related to some important applications to the Information Technologies.
- Prerequisites
- Basics in numerical analysis.
- Teaching methods
- Face-to-face lectures and laboratory sessions.
- Learning verification modality
- Oral exam and seminar. The oral exam can be substituted by some exercises, a project or a seminar, upon availability.
- Extended program
- Least square approximation and singular value decomposition (principal component analysis).
QR factorization and Nonnegative matrix factorization. Matrices with positivity structure, eigenvalue computation. Non-linear and manifold optimization.
During the course, some applications to data science and information technologies will be taken into account: data fitting, complex networks; classification problems; machine learning.
Spline interpolation. B-splines. Trigonometric interpolation. Fast Fourier Transform. Application to digital filtering, curves and surfaces in computer graphics.