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Semester | Frühjahrsemester 2023 |
Weitere Semesterveranstaltungen zu diesen KP |
67923-01 (Vorlesung) 67923-02 (Übung) |
Angebotsmuster | unregelmässig |
Dozierende | Aurelien Lucchi (aurelien.lucchi@unibas.ch, BeurteilerIn) |
Inhalt | This course provides an in-depth theoretical treatment of classical and modern optimization methods. Specifically, we will discuss the following concepts: Basic convex analysis Subgradient methods Gradient Descent Convergence rate for gradient-based methods Optimality and lower bounds Stochastic Optimization methods Non-convex Optimization |
Lernziele | - Equip students with a fundamental understanding of why optimization algorithms work, and what their limits are - Ability to select optimization algorithms for practical applications that students might encounter in their future career - Ability to understand and derive mathematical proofs for optimization algorithms |
Literatur | The first part of the class will cover some of the chapters discussed in the following books: Numerical Optimization, by Jorge Nocedal and Stephen J. Wright Convex Optimization: Algorithms and Complexity, by Sebastian Bubeck Convex Optimization, by Stephen Boyd and Lieven Vandenberghe The second part of the class will mostly be based on research papers. |
Bemerkungen | Exceptionally, the first lecture will be given on Monday, February 20 from 4.15pm to 6pm in Alte Uni, Seminarraum -201. There won't be any lecture on Thursday, February 23rd. Starting week 2: Exercise sessions will start the second week of the semester and will be scheduled every Monday (4.15pm to 6pm). The lectures will be scheduled on Thursdays from 4.15pm to 6pm. |
Weblink | https://dmi.unibas.ch/de/studium/compute |
Teilnahmevoraussetzungen | A solid background in analysis and linear algebra; some background in theoretical computer science (computational complexity, analysis of algorithms); the ability to understand and write mathematical proofs. |
Unterrichtssprache | Englisch |
Einsatz digitaler Medien | kein spezifischer Einsatz |
Intervall | Wochentag | Zeit | Raum |
---|---|---|---|
wöchentlich | Donnerstag | 16.15-18.00 | Spiegelgasse 1, Seminarraum 00.003 |
Datum | Zeit | Raum |
---|---|---|
Montag 20.02.2023 | 16.15-18.00 Uhr | Alte Universität, Seminarraum -201 |
Donnerstag 23.02.2023 | 16.15-18.00 Uhr | Spiegelgasse 1, Seminarraum 00.003 |
Donnerstag 02.03.2023 | 16.15-18.00 Uhr | Fasnachstferien |
Montag 06.03.2023 | 16.15-18.00 Uhr | Kollegienhaus, Seminarraum 103 |
Donnerstag 09.03.2023 | 16.15-18.00 Uhr | Spiegelgasse 1, Seminarraum 00.003 |
Donnerstag 16.03.2023 | 16.15-18.00 Uhr | Spiegelgasse 1, Seminarraum 00.003 |
Donnerstag 23.03.2023 | 16.15-18.00 Uhr | Spiegelgasse 1, Seminarraum 00.003 |
Donnerstag 30.03.2023 | 16.15-18.00 Uhr | Spiegelgasse 1, Seminarraum 00.003 |
Donnerstag 06.04.2023 | 16.15-18.00 Uhr | Ostern |
Donnerstag 13.04.2023 | 16.15-18.00 Uhr | Spiegelgasse 1, Seminarraum 00.003 |
Donnerstag 20.04.2023 | 16.15-18.00 Uhr | Spiegelgasse 1, Seminarraum 00.003 |
Donnerstag 27.04.2023 | 16.15-18.00 Uhr | Spiegelgasse 1, Seminarraum 00.003 |
Donnerstag 04.05.2023 | 16.15-18.00 Uhr | Spiegelgasse 1, Seminarraum 00.003 |
Donnerstag 11.05.2023 | 16.15-18.00 Uhr | Spiegelgasse 1, Seminarraum 00.003 |
Donnerstag 18.05.2023 | 16.15-18.00 Uhr | Auffahrt |
Donnerstag 25.05.2023 | 16.15-18.00 Uhr | Spiegelgasse 1, Seminarraum 00.003 |
Donnerstag 01.06.2023 | 16.15-18.00 Uhr | Spiegelgasse 1, Seminarraum 00.003 |
Module |
Modul: Applications of Distributed Systems (Masterstudium: Computer Science) Modul: Applications of Machine Intelligence (Masterstudium: Computer Science) Modul: Concepts of Machine Intelligence (Masterstudium: Computer Science) Modul: Methods of Machine Intelligence (Masterstudium: Computer Science) |
Prüfung | Lehrveranst.-begleitend |
Hinweise zur Prüfung | Continuous assessment Note the following split: 30% homework 30% project (writeup and presentation) 40% written exam A 50% score on HW sets is required to participate in the final exam. Expected date: Monday, 10 July 2023, 10-12 a.m., Spiegelgasse 1, room 00.003. |
An-/Abmeldung zur Prüfung | Anm.: Belegen Lehrveranstaltung; Abm.: stornieren |
Wiederholungsprüfung | keine Wiederholungsprüfung |
Skala | 1-6 0,5 |
Belegen bei Nichtbestehen | beliebig wiederholbar |
Zuständige Fakultät | Philosophisch-Naturwissenschaftliche Fakultät, studiendekanat-philnat@unibas.ch |
Anbietende Organisationseinheit | Fachbereich Informatik |