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| Semester | Frühjahrsemester 2023 |
| 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 |
| Teilnahmebedingungen | 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) |
| Leistungsüberprüfung | Lehrveranst.-begleitend |
| Hinweise zur Leistungsüberprüfung | 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 Leistungsüberprüfung | Anm.: Belegen Lehrveranstaltung; Abm.: stornieren |
| Wiederholungsprüfung | keine Wiederholungsprüfung |
| Skala | 1-6 0,5 |
| Wiederholtes Belegen | beliebig wiederholbar |
| Zuständige Fakultät | Philosophisch-Naturwissenschaftliche Fakultät, studiendekanat-philnat@unibas.ch |
| Anbietende Organisationseinheit | Fachbereich Informatik |