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67923-01 - Lecture: Continuous Optimization (8 CP)
| Semester | spring semester 2026 |
| Further events belonging to these CP |
67923-01 (Lecture) 67923-02 (Practical course) |
| Course frequency | Irregular |
| Lecturers | Aurelien Lucchi (aurelien.lucchi@unibas.ch, Assessor) |
| Content | 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 |
| Learning objectives | - 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 |
| Bibliography | 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. |
| Comments | Exercise sessions will start the second week of the semester and will be scheduled every Monday (4.15pm to 6pm). |
| Weblink | https://dmi.unibas.ch/de/studium/compute |
| Admission requirements | 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. |
| Language of instruction | English |
| Use of digital media | No specific media used |
| Interval | Weekday | Time | Room |
|---|---|---|---|
| wöchentlich | Wednesday | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Dates
| Date | Time | Room |
|---|---|---|
| Wednesday 18.02.2026 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
| Wednesday 25.02.2026 | 10.15-12.00 | Fasnachtsferien |
| Wednesday 04.03.2026 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
| Wednesday 11.03.2026 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
| Wednesday 18.03.2026 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
| Wednesday 25.03.2026 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
| Wednesday 01.04.2026 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
| Wednesday 08.04.2026 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
| Wednesday 15.04.2026 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
| Wednesday 22.04.2026 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
| Wednesday 29.04.2026 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
| Wednesday 06.05.2026 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
| Wednesday 13.05.2026 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
| Wednesday 20.05.2026 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
| Wednesday 27.05.2026 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
| Modules |
Doctorate Computer Science: Recommendations (PhD subject: Computer Science) Module: Applications of Distributed Systems (Master's Studies: Computer Science) Module: Applications of Machine Intelligence (Master's Studies: Computer Science) Module: Concepts of Machine Intelligence (Master's degree subject: Computer Science) Module: Concepts of Machine Intelligence (Master's Studies: Computer Science) Module: Methods of Machine Intelligence (Master's Studies: Computer Science) Module: Systems Foundations (Master's Studies: Data Science) |
| Assessment format | continuous assessment |
| Assessment details | Continuous assessment Note the following split: 15% continuous assesment (short exercises and Q&As given in class) 20% homework 30% project (writeup and presentation) 35% written exam A 50% score on HW sets is required to participate in the final exam. Expected date: tba |
| Assessment registration/deregistration | Reg.: course registration, dereg: cancel course registration |
| Repeat examination | no repeat examination |
| Scale | 1-6 0,5 |
| Repeated registration | as often as necessary |
| Responsible faculty | Faculty of Science, studiendekanat-philnat@unibas.ch |
| Offered by | Fachbereich Informatik |