Bernd Gärtner: Catalogue data in Autumn Semester 2023

Name Prof. Dr. Bernd Gärtner
Address
Inst. f. Theoretische Informatik
ETH Zürich, OAT Z 15
Andreasstrasse 5
8092 Zürich
SWITZERLAND
Telephone+41 44 632 70 26
Fax+41 44 632 10 63
E-mailgaertner@inf.ethz.ch
URLhttp://people.inf.ethz.ch/gaertner/
DepartmentComputer Science
RelationshipAdjunct Professor

NumberTitleECTSHoursLecturers
252-0209-00LAlgorithms, Probability, and Computing Information 8 credits4V + 2U + 1AB. Gärtner, R. Kyng, A. Steger, D. Steurer, E. Welzl
AbstractAdvanced design and analysis methods for algorithms and data structures: Random(ized) Search Trees, Point Location, Minimum Cut, Linear Programming, Randomized Algebraic Algorithms (matchings), Probabilistically Checkable Proofs (introduction).
ObjectiveStudying and understanding of fundamental advanced concepts in algorithms, data structures and complexity theory.
Lecture notesWill be handed out.
LiteratureIntroduction to Algorithms by T. H. Cormen, C. E. Leiserson, R. L. Rivest;
Randomized Algorithms by R. Motwani und P. Raghavan;
Computational Geometry - Algorithms and Applications by M. de Berg, M. van Kreveld, M. Overmars, O. Schwarzkopf.
252-1425-00LGeometry: Combinatorics and Algorithms Information 8 credits3V + 2U + 2AB. Gärtner, E. Welzl, M. Hoffmann, P. Schnider
AbstractGeometric structures are useful in many areas, and there is a need to understand their structural properties, and to work with them algorithmically. The lecture addresses theoretical foundations concerning geometric structures. Central objects of interest are triangulations. We study combinatorial (Does a certain object exist?) and algorithmic questions (Can we find a certain object efficiently?)
ObjectiveThe goal is to make students familiar with fundamental concepts, techniques and results in combinatorial and computational geometry, so as to enable them to model, analyze, and solve theoretical and practical problems in the area and in various application domains.
In particular, we want to prepare students for conducting independent research, for instance, within the scope of a thesis project.
ContentPlanar and geometric graphs, embeddings and their representation (Whitney's Theorem, canonical orderings, DCEL), polygon triangulations and the art gallery theorem, convexity in R^d, planar convex hull algorithms (Jarvis Wrap, Graham Scan, Chan's Algorithm), point set triangulations, Delaunay triangulations (Lawson flips, lifting map, randomized incremental construction), Voronoi diagrams, the Crossing Lemma and incidence bounds, line arrangements (duality, Zone Theorem, ham-sandwich cuts), 3-SUM hardness, counting planar triangulations.
Lecture notesyes
LiteratureMark de Berg, Marc van Kreveld, Mark Overmars, Otfried Cheong, Computational Geometry: Algorithms and Applications, Springer, 3rd ed., 2008.
Satyan Devadoss, Joseph O'Rourke, Discrete and Computational Geometry, Princeton University Press, 2011.
Stefan Felsner, Geometric Graphs and Arrangements: Some Chapters from Combinatorial Geometry, Teubner, 2004.
Jiri Matousek, Lectures on Discrete Geometry, Springer, 2002.
Takao Nishizeki, Md. Saidur Rahman, Planar Graph Drawing, World Scientific, 2004.
Prerequisites / NoticePrerequisites: The course assumes basic knowledge of discrete mathematics and algorithms, as supplied in the first semesters of Bachelor Studies at ETH.
Outlook: In the following spring semester there is a seminar "Geometry: Combinatorics and Algorithms" that builds on this course. There are ample possibilities for Semester-, Bachelor- and Master Thesis projects in the area.
252-4202-00LSeminar in Theoretical Computer Science Information Restricted registration - show details 2 credits2SE. Welzl, B. Gärtner, M. Hoffmann, J. Lengler, A. Steger, D. Steurer, B. Sudakov
AbstractPresentation of recent publications in theoretical computer science, including results by diploma, masters and doctoral candidates.
ObjectiveThe goal is to introduce students to current research, and to enable them to read, understand, and present scientific papers.
Prerequisites / NoticeThis seminar takes place as part of the joint research seminar of several theory groups. Intended participation is for students with excellent performance only. Formal restriction is: prior successful participation in a master level seminar in theoretical computer science.
265-0101-00LData Science Restricted registration - show details 4 credits3VB. Gärtner
AbstractIn this module, basic paradigms and techniques in working with data will be discussed, especially towards data security, managing data decentrally, and learning from data.
ObjectiveParticipants will understand some of the concepts in detail and see the mathematics behind them.
ContentThe module in particular covers cryptography and digital signatures,
networking and distributed algorithms, distributed ledger technology,
as well as machine learning (supervised and unsupervised
learning). For each topic, there will be a hands-on and in-depth
introduction that allows participants to gain a technical
understanding of key ideas. This is supported by simple and concrete
examples as well as programming assignments.
401-0131-00LLinear Algebra Information 7 credits4V + 2UA. Bandeira, B. Gärtner
AbstractIntroduction to linear algebra: vectors and matrices, solving systems of linear equations, vector spaces and subspaces, orthogonality and least squares, determinants, eigenvalues and eigenvectors, singular value decomposition and linear transformations. Applications in and links to computer science will be presented in parallel.
Objective- Understand and apply fundamental concepts of linear algebra
- Learn about applications of linear algebra in computer science
ContentVectors and matrices, solving systems of linear equations, vector spaces and subspaces, orthogonality and least squares, determinants, eigenvalues and eigenvectors, singular value decomposition and linear transformations. Applications in and links to computer science.
LiteratureGilbert Strang, Introduction to Linear Algebra, 6th Edition, Wellesley - Cambridge Press. Further literature and links can be found on the course webpage.
CompetenciesCompetencies
Subject-specific CompetenciesConcepts and Theoriesassessed
Techniques and Technologiesassessed
Method-specific CompetenciesAnalytical Competenciesassessed
Decision-makingfostered
Media and Digital Technologiesfostered
Problem-solvingassessed
Project Managementfostered
Social CompetenciesCommunicationfostered
Cooperation and Teamworkfostered
Customer Orientationfostered
Leadership and Responsibilityfostered
Self-presentation and Social Influence fostered
Sensitivity to Diversityfostered
Negotiationfostered
Personal CompetenciesAdaptability and Flexibilityfostered
Creative Thinkingassessed
Critical Thinkingfostered
Integrity and Work Ethicsfostered
Self-awareness and Self-reflection fostered
Self-direction and Self-management fostered