## 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 organizationSchedule (2016-2017): Mondays from 13h30 until 16h30, amphi Tocqueville. First class on Oct. 3 2016. Location: Amphi Tocqueville at E.N.S. Cachan. campus map. Getting there: RER B, station **Bagneux**. See the access plan to E.N.S. Cachan.
## OrganisationThe course is split in three parts. Six lectures of three hours each. Modelling Convex sets, functions and problems Duality
Algorithms Interior point methods Complexity First-order methods, acceleration
Applications Machine learning and statistics Signal processing Combinatorial problems Finance
## ReferencesConvex Optimization, S. Boyd and L. Vandenberghe, Cambridge University Press. Introductory Lectures on Convex Optimization, Y. Nesterov, Springer. Lectures on Modern Convex Optimization, A. Nemirovski and A. Ben-Tal, SIAM.
## Notes## ExercicesMost of the exercises are taken from the textbook by Boyd et Vandenberghe. DM1: Due Monday October 24 at 13h30. From the Convex Optimization textbook: Ex. 2.12, 3.21, 3.32, 3.36 DM2: Due Monday November 7 at 13h30. Ex. 5.5, 5.7, 5.9, 5.11, 5.13. DM3: Due Monday November 21 at 13h30. DM 3.
## ExamFinal exam, on Friday, November 25 2016, 14h00-17h00 in class. Closed book. You are allowed one page of notes (recto-verso). |