Veranstaltungsverzeichnis

Lehrveranstaltungen SoSe 2024

Technomathematik, B.Sc./M.Sc. (Studienbeginn vor 2022)

Veranstaltungen anzeigen: alle | in englischer Sprache | für ältere Erwachsene | mit Nachhaltigkeitszielen

Master: Pflichtveranstaltungen

VAKTitel der VeranstaltungDozentIn
03-M-MP-1Modeling Project (Part 1) (in englischer Sprache)

Seminar
ECTS: 6

Termine:
wöchentlich Di 10:00 - 12:00 MZH 2340 Seminar

Over the course of two semesters, the participants of the modeling project work in teams on a project in which they are supposed to use the mathematical knowledge they have already acquired in applications outside of mathematics. The project partners can be industrial companies or research institutes.

Tobias Kluth
Peter Maaß

Master: Wahlpflichtveranstaltungen

VAKTitel der VeranstaltungDozentIn
03-IMAT-APX (03-ME-602.99a)Approximation Algorithms (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Di 10:00 - 12:00 MZH 3150 Kurs
wöchentlich Do 14:00 - 16:00 MZH 1470 MZH 5500 Übung

Profil: SQ, KIKR.
Schwerpunkt: IMA-SQ, IMVT-AI, IMVT-VMC
weitere Studiengänge: M-M-Alg-Num, M-T
https://lvb.informatik.uni-bremen.de/imat/03-imat-apx.pdf

A large number of problems arising in practical scenarios like communication, transportation, planning, logistics etc. can be modeled as combinatorial optimization problems. In most cases, these problems are computationally intractable and one often resorts to heuristics that provide sufficiently good solutions in reasonable amount of runtime. However, in most cases, such heuristics do not provide a worst case guarantee on the performance in comparison to the optimum solution. In this course, we shall study algorithms for combinatorial optimization problems which can provide strong mathematical guarantees on performance. The course aims at developing a toolkit for solving such problems. The lectures will consist of designing polynomial-time algorithms and proving rigorous bounds on their worst case performances.
We review many classical results in the field of approximation algorithms, highlighting different techniques commonly used for the design of such algorithms. Among others, we will treat the following topics:
• Greedy algorithms and Local Search
• Rounding Data and Dynamic Programming
• Deterministic Rounding of Linear Programs (LPs)
• Random Sampling and Randomized Rounding of LPs
• Primal-Dual Methods
• Hardness of Approximation
• Problem Solving under Uncertainty

Dr. Felix Christian Hommelsheim
03-M-SP-12High-Performance-Visualisierung (in englischer Sprache)
High-Performance Visualization
Interaktive Exploration zur Analyse von extrem großen wissenschaftlichen Daten

Vorlesung
ECTS: 4,5 / 6

Termine:
wöchentlich Do 14:00 - 16:00 MZH 1110 Lecture and Exercise

Einzeltermine:
Do 11.07.24 14:00 - 18:00 MZH 1110
Do 22.08.24 - Fr 23.08.24 (Do, Fr) 08:00 - 14:00 MZH 5500

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

Prof. Dr. Andreas Gerndt
03-M-SP-14Scientific Programming and Advanced Numerical Methods - an Introduction with Case Studies (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 14:00 - 16:00 MZH 2340 Lecture
wöchentlich Do 12:00 - 14:00 MZH 2340 Lecture

Einzeltermine:
Mi 10.07.24 14:00 - 16:00 ZOOM
Mi 17.07.24 14:00 - 16:00 ZOOM
Mo 22.07.24 - Fr 26.07.24 (Mo, Di, Mi, Do, Fr) 10:00 - 16:30

This course provides an introduction to the practice of scientific programming.

Alfred Schmidt
Prof. Dr. Stephan Frickenhaus
03-M-SP-15Analytic and Discrete Convex Geometry (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 4140 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 1100 MZH 5220 (Didaktik-Labor) Lecture
wöchentlich Mi 12:00 - 14:00 MZH 3150 Exercise

Convex Geometry plays an essential role in several branches of Mathematics, from Discrete Mathematics to Harmonic Analysis. We will discuss some major analytic and discrete aspects of convex geometry and some applications. Our topics will range from the boundary structure of convex bodies, particularly polytopes, to Hadwiger's volume characterisation, via geometric and functional inequalities, as well as geometric and analytic symmetrization techniques.

Eugenia Saorin Gomez
03-M-SP-16Mathematical Foundations of Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 14:00 - 16:00 MZH 2340 Exercise

This course deals with the mathematical foundations of machine learning with a strong focus on classical theory and well-established algorithms like, for example, support vector machines for classification, ridge regression, principal component analysis for dimensionality reduction and k-means clustering. In addition, deep learning with neural networks will be briefly discussed towards the end of the course.

Peter Maaß
Dr. Matthias Beckmann
03-M-SP-20Digital Optimal Control and Optimal Feedback Control (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 10:00 - 12:00 Externer Ort: NEOS Gebäude 3. Etage Lecture
wöchentlich Do 10:00 - 12:00 Externer Ort: NEOS Gebäude 3. Etage Lecture
wöchentlich Do 12:00 - 14:00 Externer Ort: NEOS Gebäude 3. Etage Exercise

Die Veranstaltung findet im NEOS Gebäude statt.

Prof. Dr. Christof Büskens
03-M-SP-22Linear and Generalized Linear Regression (Statistics II) (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 08:00 - 10:00 MZH 7200 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 7200 Exercise
wöchentlich Do 08:00 - 10:00 MZH 7200 Lecture

Einzeltermine:
Do 25.07.24 10:00 - 12:00 MZH 7200
Maryam Movahedifar
03-M-SP-32Spectral Theory (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 14:00 - 16:00 MZH 4140 Lecture
wöchentlich Do 10:00 - 12:00 MZH 4140 Lecture
wöchentlich Do 16:00 - 18:00 MZH 4140 Exercise
PD Dr. Hendrik Vogt
03-M-SP-33Semiparametric Models (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Di 09:00 - 10:30 Vorlesung
wöchentlich Mi 14:00 - 16:00 Übung
wöchentlich Fr 12:30 - 14:00 Vorlesung

Die Veranstaltung findet im KKSB statt.

The course will provide an introduction into the theory of semiparametric models. We will introduce and discuss the mathematical statistical theory for such models and will illustrate the utility of semiparametric models with a number of concrete models and data examples. Hence, the lecture and exercises will cover theoretical and practical aspects of semiparametric models. We will use the open statistical software R for the data applications.

Prof. Dr. Werner Brannath
03-M-SP-34Differential Geometry (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Di 10:00 - 12:00 MZH 1110 MZH 4140 Lecture
wöchentlich Di 12:00 - 14:00 MZH 1470 Exercise
wöchentlich Mi 16:00 - 18:00 MZH 4140 Lecture

This course will cover manifolds, vector bundles, embeddings and submersions, integral curves and flows, basics of Lie groups, differential forms and integration, Riemannian metrics, geodesics, connections, curvature, and further topics.

Prof. Dr. Anke Dorothea Pohl
03-M-SP-35Selected Topics in Convex Optimization (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Mi 12:00 - 14:00 MZH 2490 (Seminarraum) Exercise

The course will discuss convex optimisation problems and present and analyse algorithms that solve them. Topics will include proximal splitting, acceleration, stochastic algorithms, and performance estimation.

Sebastian Banert
Dirk Lorenz
03-M-SP-36Selected Topics on Optimization for Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Do 14:00 - 16:00 MZH 2340 Lecture
wöchentlich Fr 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Fr 12:00 - 14:00 MZH 2340 Exercise
Dirk Lorenz
Lionel Ngoupeyou Tondji

Master: Seminare

VAKTitel der VeranstaltungDozentIn
03-M-AC-21Deep Learning for Inverse Problems (in englischer Sprache)

Seminar
ECTS: 4,5/6

Termine:
wöchentlich Mo 14:00 - 16:00 MZH 2340 Seminar
Peter Maaß
03-M-AC-22Advanced Communication Analysis (in englischer Sprache)

Seminar
ECTS: 4,5/6

Termine:
wöchentlich Mi 12:00 - 14:00 MZH 4140 Seminar

Einzeltermine:
Fr 24.05.24 12:00 - 16:00 MZH 1380/1400

In the Seminar Analysis advanced topics in the area of analysis are discussed. The precise topic for Summer semester 2024 will be decided upon with the participants

Prof. Dr. Anke Dorothea Pohl
03-M-AC-23Advanced Robust Control (in englischer Sprache)

Seminar
ECTS: 4,5 / 6

Termine:
wöchentlich Do 10:00 - 12:00 MZH 2340 Seminar
Dr. Chathura Wanigasekara
03-M-AC-28Advanced Numerical Methods for Partial Differential Equations (in englischer Sprache)

Seminar
ECTS: 4,5 / 6

Termine:
wöchentlich Mo 16:00 - 18:00 MZH 2340 Seminar

Seminar on advanced numerical methods for partial differential equations

Alfred Schmidt

Oberseminare

VAKTitel der VeranstaltungDozentIn
Oberseminar Mathematical Parameter Identification (RTG-Seminar) (in englischer Sprache)
Research Seminar - Mathematical Parameter Identification (RTG)

Seminar

Termine:
wöchentlich Mi 12:00 - 14:00 MZH 2340


Dr. rer. nat. Pascal Fernsel

General Studies

VAKTitel der VeranstaltungDozentIn
03-IBFW-HTO (03-BE-699.12)Hands-on Tutorial on Optimization (in englischer Sprache)

Blockveranstaltung
ECTS: 3

Einzeltermine:
Mo 23.09.24 - Fr 27.09.24 (Mo, Di, Mi, Do, Fr) 09:00 - 17:00 MZH 5500

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 and Gurobi) 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: September 23-27, 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.

Prof. Dr. Nicole Megow
03-M-GS-7Introduction to R (in englischer Sprache)

Vorlesung
ECTS: 3

Termine:
wöchentlich Fr 10:00 - 13:00 GW1 A0150 Seminar

3 SWS Seminar
Raum wird nach Anmeldung in Stud.IP bekannt gegeben.
Homepage des KKSB und Uni-Lageplan

Prof. Dr. Werner Brannath
Eike Voß
SZHB 0622ONLINE: English for Mathematicians and Industrial Mathematicians (Zertifikatskurs UNIcert II) (B2.3) (in englischer Sprache)
Eingangsniveau: B2.2

Kurs
ECTS: 3

Termine:
wöchentlich Di 16:15 - 17:55 Externer Ort: Onlinekurs (2 SWS)


Edwin Shillington