60 Lehrveranstaltungen in Deutsch und Englisch für Bachelor- und Masterstudentinnen aller Fächer. Als General Studies sowie teilweise als Fachstudium im Sommersemester 2025 sowie im Wintersemester 2025/26 anerkannt.
Alle Einzelangaben, Zeiten und Anmeldungen jederzeit nur über die Website https://www.informatica-feminale.de.
60 courses in German and English for women Bachelor and Master students from all fields of study. Courses are part of General Studies, some are accepted in Informatics; in the summer semester 2025 as well as in winter semester 2025/26.
Further information, schedules and registration only on the website https://www.informatica-feminale.de.

3 SWS Seminar
Raum im KKSB Linz 4
Homepage des KKSB und Uni-Lageplan

https://lvb.informatik.uni-bremen.de/igs/03-ibfw-hto.pdf
A large number of problems arising in practical scenarios like communication, transportation, planning, logistics etc. can be formulated as discrete linear optimization problems. This course briefly introduces the theory of such problems. We develop a toolkit to model real-world problems as (discrete) linear programs. We also explore several ways to find integer solutions such as cutting planes, branch & bound, and column generation.

Throughout the course, we learn these skills by modeling and solving, for example, scheduling, packing, matching, routing, and network-design problems. We focus on translating practical examples into mixed-integer linear programs. We learn how to use solvers (such as CPLEX, Gurobi, Xpress and free ones) and tailor the solution process to certain properties of the problem.

This course consists of two phases:

• One week Mon-Fri (full day, 9-5) of lectures and practical labs: July 14-18, in MZH.
• A subsequent project period: One problem has to be modeled, implemented, and solved individually or in a group of at most three students. The topic will be provided by the lecturers and will be discussed on the last day of the block course. The project including the implementation has to be presented in the beginning of the winter semester.

There are no prerequisites except some basic programming skills to participate.

Die Veranstaltung findet im KKSB statt.

60 Lehrveranstaltungen in Deutsch und Englisch für Bachelor- und Masterstudentinnen aller Fächer. Als General Studies sowie teilweise als Fachstudium im Sommersemester 2025 sowie im Wintersemester 2025/26 anerkannt.
Alle Einzelangaben, Zeiten und Anmeldungen jederzeit nur über die Website https://www.informatica-feminale.de.
60 courses in German and English for women Bachelor and Master students from all fields of study. Courses are part of General Studies, some are accepted in Informatics; in the summer semester 2025 as well as in winter semester 2025/26.
Further information, schedules and registration only on the website https://www.informatica-feminale.de.

Many every-day processes can seen as a game between autonomous interacting players, where each player acts strategically in order to pursue her own objectives. This lecture is an introduction to game-theoretic concepts and techniques, mainly with connections to applications. Use-cases are distributed systems, auctions, online-markets, resource allocation, and traffic networks. The goal of the lecture is to provide an overview over state-of-the-art results in the area of algorithmic game theory. Main topics that we will cover in the course are \begin{itemize} \item Strategic Games and Efficiency of Equilibria \item Auctions, Truthfulness and VCG-mechanisms \item Cooperative Games \item Social Choice \end{itemize}

The lectures and homework sheets will be in English language. If all participants agree, the exercise session could be held in German. If there is an oral exam, the language can be chosen by the candidate. In case of a written exam the questions will be in English, answering them in German or English is fine.

Commutative algebra is a branch of algebra which studies commutative rings, ideals and modules. We will discuss the theory of ideals of a polynomial ring, graded and multigraded modules, Gröbner bases, presentations and resolutions of modules. Topics are: Polynomial rings, ideals and varieties Gröbner bases and Buchberger’s algorithm Hilbert’s Nullstellensatz Multigraded modules and Betti numbers Rank invariants Presentations and resolutions Hilbert’s syzygy theorem Schreyer’s theorem

In this course we will delve into the fascinating world of Ergodic Theory, a branch of mathematics that studies the asymptotic properties of transformations on topological and measurable spaces. From the origins of the ergodic hypothesis, which laid the foundation for classical statistical mechanics, to modern applications such as hyperbolic geometry or metric number theory, we will uncover the intricate relationships between measure-preserving systems, recurrence, entropy, and stochastic characterisations of dynamical systems. Through a combination of theoretical foundations and illuminating examples, we will explore the fundamental concepts of ergodic theory, including Measure-preserving systems and their properties Several ergodic theorems and their implications Recurrence and its role in understanding the behaviour of dynamical systems Dynamical spectra and their connections to number theory Entropy and its role in the study of dynamical systems Ergodic theory has far-reaching implications in many different fields outside mathematics, including physics, biology, economics and computer science (machine learning). The study of dynamical systems and ergodic theory has led to numerous breakthroughs in mathematics and has been recognised by several Fields Medals in recent years. By studying ergodic theory, you will gain a deeper understanding of the underlying mathematical structures and principles that govern complex systems. This course is an excellent starting point for further research in the field of dynamical systems, leading to exciting topics for master theses in the areas of the analysis/stochastics group. Join us on this journey into the fascinating world of Ergodic Theory!

The lecture addresses Interactive Visualization of Huge Scientific Datasets. More information can also be found on the Homepage: https://www.uni-bremen.de/ag-high-performance-visualization

Die Vorlesung beschäftigt sich mit den mathematischen Grundlagen der wissenschaftlichen Visualisierung und behandelt Methoden für das parallele Post-Processing großer wissenschaftlicher Datensätze. Anwendungsbeispiele werden anhand der Open-Source-Software ParaView erläutert.
Homepage zur Veranstaltung: https://www.uni-bremen.de/ag-high-performance-visualization

3 SWS Seminar
Raum im KKSB Linz 4
Homepage des KKSB und Uni-Lageplan

Inverse problems are problems where one would like to find an unknown cause for which one can only measure observed effects. This situation occurs, for example, if one can only make indirect measurements of the quantity of interest. Two simple examples: \begin{itemize} \item We measure the position of an object, but would like to know the speed. \item In tomography we measure several projections (X-ray images) of an object, but would like to know the absorption spectrum of said object. \end{itemize} Inverse problems usually suffer from ill-posedness: Solutions may not be unique, they may not exist (for example due to measurement noise), and, most drastically, their solution is unstable in the sense that it does not depend continuously on the data. We will analyze the phenomenon on ill-posedness for linear inverse problems (modeled as linear and continuous maps between Hilbert spaces) to understand the reason for instability. A central goal of the course is to establish the notion of regularization of ill-posed problems (which roughly means the approximate solution by stable methods) and to derive and analyze regularization methods such as Tikhonov regularization, or the Landweber method with early stopping. We will also treat the numerical solution of inverse problems in the lecture and the exercises.

https://lvb.informatik.uni-bremen.de/ims/03-ims-apks.pdf
Termine:
Auftakttermin: 08.04. um 12:00 Uhr in Raum 2.43 Rotunde Cartesium.

This seminar will treat methods of convex optimization that are suitable for large problems with millions of variables (the size is basically restricted that the computer memory can hold a small finite number of vectors). The guiding principle of these methods is to exploit suitable additive \emph{splitting} of the objective function and then use simple building blocks for the splitted parts to assemble an algorithm. Recently there has been much progress in this areas and in this seminar we will explore the following directions, for example: \begin{itemize} \item Stochastic optimization (stochastic gradient descent, stochastic proximal gradient method), [Chapter 7, 1] \item Accelerated methods (Accelerated gradient descent, accelerated proximal point methods), [Chapter 12, 1] \item Degenerate preconditioned proximal point methods [2] \item Kaczmarz (row-action) methods with mismatched adjoint [3] \end{itemize}

This course introduces quantum computing, covering the mathematical principles needed to understand and implement quantum algorithms. Topics include qubits, entanglement, quantum gates, and circuits. Students will explore algorithms like Deutsch-Jozsa and Shor’s, and problems such as secure communication. The course also addresses error correction and adiabatic algorithms, and includes hands-on practice using Qiskit to build and simulate quantum circuits on IBM’s Quantum Lab.

Die Veranstaltung findet im KKSB statt.