Master M2 MVA: Convex Optimization, Algorithms and Applications.DescriptionThe objective of this course is to learn to recognize, transform and solve a broad class of convex optimization problems arising in various fields such as machine learning, finance or signal processing. The course starts with a basic primer on convex analysis followed by a quick overview of convex duality theory. The second half of the course is focused on algorithms, including first-order and interior point methods, together with bounds on their complexity. The course ends with illustrations of these techniques in various applications. Course organization
OrganisationThe course will be live but course videos from 2020 are available below.
NotesProgramThe course is split in three parts.
References
ExercicesMany of the exercises are taken from the textbook by Boyd et Vandenberghe. We will be using Gradescope to grade assignments. In order to submit your work, you must create a Gradescope account. Please ensure you do so with your full name. You will then be able to join the course using course number PYNZRN and use “National Institute for Research in Digital Science and Technology” as the school. Late homework will not be graded.
ExamFinal exam, on Monday Dec. 16 2024, 13:00-16:00, salle 1G58 (grand amphi Alain Aspect) ENS Paris-Saclay. |