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Semester | spring semester 2025 |
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 |
Date | Time | Room |
---|---|---|
Wednesday 19.02.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Wednesday 26.02.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Wednesday 05.03.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Wednesday 12.03.2025 | 10.15-12.00 | Fasnachstferien |
Wednesday 19.03.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Wednesday 26.03.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Wednesday 02.04.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Wednesday 09.04.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Wednesday 16.04.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Wednesday 23.04.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Wednesday 30.04.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Wednesday 07.05.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Wednesday 14.05.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Wednesday 21.05.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Wednesday 28.05.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Monday 07.07.2025 | 10.00-12.00 | Biozentrum, Hörsaal U1.101 |
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 |