Latest

2024.03.06: Minor typo corrected in homework.
2024.01.10: Course homework online.
2023.12.03: Boards from lectures 5-7 (2022-2023 versions), lecture notes, solutions to the exercises. 2023.11.03: Companion notebook for upcoming lectures+tutorial for last session.
2023.10.05: Board from fourth lecture+companion notebook online.
2023.10.04: Board from third lecture+companion notebook online.
2023.09.22: Board from second lecture+companion notebook online.
2023.09.21: Board from the first lecture online.
2023.09.14: Course webpage online.

Instructors

Florentin Goyens
florentin.goyens@dauphine.psl.eu

Clément Royer
clement.royer@lamsade.dauphine.fr

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Optimization for Machine Learning

M2 IASD Apprentissage, Université Paris Dauphine-PSL, 2023-2024

Aim of the course

Study the main optimization techniques used in machine learning and data science, as well as their underlying principles.

Course project (deadline: March 10, 2024)

Assignment PDF

Course material

     Lecture notes (updated regularly) PDF

     Virtual board for lecture 1 PDF

     Virtual board for lecture 2 PDF
     Companion notebook for lecture 2 [Sources]

     Virtual board for lecture 3 PDF
     Companion notebook for lecture 3 [Sources]

     Virtual board for lecture 4 PDF
     Companion notebook for lecture 4 [Sources]

     Virtual board for lecture 5 (2022-2023 version) PDF
     Companion notebook for lecture 5 [Sources]

     Virtual board for lecture 6 (2022-2023 version) PDF
     Companion notebook for lecture 6 [Sources]

     Virtual board for lecture 7 (2022-2023 version) PDF
     Companion notebook for lecture 7 [Sources]

     Exercises (last year's exam, English version with solutions) PDF

Materials on this page are available under Creative Commons CC BY-NC 4.0 license.
La version française de cette page se trouve ici.