OPTIMIZATION

Course objectives

To provide methodologies and algorithmic tools for the formulation, analysis and solution of several optimization problems, with particular reference to those concerning artificial intelligence. The mathematical programming topics and the optimization algorithms characterizing the course will be useful to deeply understand the mathematical models and optimization methods underlying artificial intelligence tools. The students of the course will be able to design and implement algorithms for complex optimization problems and, in particular, for machine learning.

Channel 1
MARCO SCIANDRONE Lecturers' profile

Program - Frequency - Exams

Course program
Optimization models Convexity of sets and functions Linear programming Integer Linear Programming Unconstrained optimizazion: existence of optimal solutions optimality conditions unconstrained optimization algorithms global convergence conditions line search techniques gradient methods stochastic gradient methods
Prerequisites
Linear algebra
Books
Introduction to methods for nonlinear optimization Luigi Grippo, Marco Sciandrone, Springer, 2023 Lecture notes
Frequency
Optional
Exam mode
Written test with theoretical questions and exercises
Lesson mode
Lectures in classroom
  • Lesson code1017662
  • Academic year2025/2026
  • Coursecorso|33593
  • CurriculumSingle curriculum
  • Year2nd year
  • Semester2nd semester
  • SSDMAT/09
  • CFU6
  • Subject areaFormazione Modellistico-Applicativa