Current courses
- Optimization
(M1/2A ENSIMAG)
Docs: Partial lectures notes -- Exercices
Notebooks: tp1 -- tp2 -- tp3 -- tp4
Prerequisites: basics of python -- numpy
Books (in French)
Objectif Agrégation
V. Beck, J. Malick, G. Peyré
Editions H&K, 2005
(towards success in "Agrégation de maths")
Data Science (cours et exercices)
9 co-authors from Grenoble
Editions Eyrolles, 2018
(overview of the foundations of data science)
Previous courses
- [Winter 2018, 2019, 2020, 2021] Advanced Operations Research
(M2 of CS, track Operations Research); Exercises
- [Winters 2016, 2017, 2018, 2019] Convex and Distributed Optimization
(Master 2 of Applied Maths)
presentation of the course; more on course website
- [Fall 2017] Basics on Matrix Analysis and Optimization (with F. Iutzeler)
(M2 of CS of University Grenoble Alpes)
Presentation of the course;
Exercices; material for practical session on github
- [Winters 2013, 2014, 2015] Mixed-integer linear programming
(master 2 of CS of UGA, option operations research)
List of research articles to study
- [Spring 2012] I mention here this nice exam:
"Epreuve du concours d'entrée" (ENS Cachan)
- [Jan 2011] Optimization and convexity
(master of computer sciences of ENS Lyon)
Slides of introduction
Tutorials: TP basis of numerical optimization --
TD convex analysis -- TD duality -- Exam
- [Winter 2010] Optimization methods in finance
(master 2 Math-Fi of ENSIMAG)
Expanded summary (in french): Summary (4 pages)
- [2009] Basic numerical tools of optimization
Winter School of fluid mechanics, organized LIMSI, CNRS
lecture notes (in english with abstract in french)
- [Every 1st semester from 2007 to 2015] Numerical Optimization
(master of ENSIMAG and Grenoble University)
Expanded summary: Summary (4 pages)
lecture notes (in english with abstract in french)
