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67923-01 - Lecture: Continuous Optimization (6 CP)
| Semester | spring semester 2024 |
| 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 | Thursday | 16.15-18.00 | Spiegelgasse 1, Seminarraum 00.003 |
Dates
| Date | Time | Room |
|---|---|---|
| Thursday 29.02.2024 | 16.15-18.00 | Spiegelgasse 1, Seminarraum 00.003 |
| Thursday 07.03.2024 | 16.15-18.00 | Spiegelgasse 1, Seminarraum 00.003 |
| Thursday 14.03.2024 | 16.15-18.00 | Spiegelgasse 1, Seminarraum 00.003 |
| Thursday 21.03.2024 | 16.15-18.00 | Spiegelgasse 1, Seminarraum 00.003 |
| Thursday 28.03.2024 | 16.15-18.00 | Ostern |
| Thursday 04.04.2024 | 16.15-18.00 | Spiegelgasse 1, Seminarraum 00.003 |
| Thursday 11.04.2024 | 16.15-18.00 | Spiegelgasse 1, Seminarraum 00.003 |
| Thursday 18.04.2024 | 16.15-18.00 | Spiegelgasse 1, Seminarraum 00.003 |
| Thursday 25.04.2024 | 16.15-18.00 | Spiegelgasse 1, Seminarraum 00.003 |
| Thursday 02.05.2024 | 16.15-18.00 | Spiegelgasse 1, Seminarraum 00.003 |
| Thursday 09.05.2024 | 16.15-18.00 | Auffahrt |
| Thursday 16.05.2024 | 16.15-18.00 | Spiegelgasse 1, Seminarraum 00.003 |
| Thursday 23.05.2024 | 16.15-18.00 | Spiegelgasse 1, Seminarraum 00.003 |
| Thursday 30.05.2024 | 16.15-18.00 | Spiegelgasse 1, Seminarraum 00.003 |
| 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: 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, 8 July 2024, 10-12 a.m.. |
| 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 |