• ECTS

    5 credits

  • Training structure

    Faculty of Science

Description

Acquire basic concepts in mathematical optimization and its applications.

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Objectives

This EU will address the following points:

     - Constraint-free extremum: concept of convexity, optimality conditions, descent methods, separable functionals, stochastic gradient

     - Extremums with constraints: strong and weak formulation, related extrema, Lagrange multipliers, and implementation with Newton. KKT conditions, duality, Uzawa. Linear programming.

     - Introduction to Mathematical Learning

     - Some areas of application:

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Teaching hours

  • Convex optimization - CMLecture6 p.m.
  • Convex optimization - Practical workPractical Work12 p.m.
  • Convex optimization - TutorialTutorial3 p.m.

Mandatory prerequisites

Analysis of L1, L2, and the first semester of L3, in particular:

- HAX404X Topology ofRn and functions of several variables

- HAX502X Differential Calculus and Differential Equations

 

 

Recommended prerequisites: first semester of L3

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Additional information

Hourly volumes:

            CM: 18

            TD: 15

            TP: 12

            Land: -

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