Rasmus Kyng: Katalogdaten im Herbstsemester 2020

NameHerr Prof. Dr. Rasmus Kyng
LehrgebietTheoretische Informatik
Adresse
Professur Theoretische Informatik
ETH Zürich, OAT Z 19.2
Andreasstrasse 5
8092 Zürich
SWITZERLAND
Telefon+41 44 632 73 30
E-Mailkyng@inf.ethz.ch
DepartementInformatik
BeziehungAssistenzprofessor (Tenure Track)

NummerTitelECTSUmfangDozierende
252-0209-00LAlgorithms, Probability, and Computing Information 8 KP4V + 2U + 1AB. Gärtner, M. Ghaffari, R. Kyng, D. Steurer
KurzbeschreibungAdvanced 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).
LernzielStudying and understanding of fundamental advanced concepts in algorithms, data structures and complexity theory.
SkriptWill be handed out.
LiteraturIntroduction 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.
263-4410-00LSeminar on Advanced Graph Algorithms and Optimization Information Belegung eingeschränkt - Details anzeigen
Number of participants limited to 6! The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar.
2 KP2SR. Kyng
KurzbeschreibungThis seminar aims to familiarize students with current research topics in fast graph algorithms and optimization.
LernzielRead papers on cutting edge research topics; learn how to give a scientific talk.
InhaltWe will study recent papers that made significant contributions in the areas in fast graph algorithms and optimization.
Voraussetzungen / BesonderesAs prerequisite we require that you passed the course "Advanced Graph Algorithms and Optimization". In exceptional cases, students who passed one of the courses "Randomized Algorithms and Probabilistic Methods", "Optimization for Data Science", or "Advanced Algorithms" may also participate, at the discretion of the lecturer.