Mohsen Ghaffari: Katalogdaten im Herbstsemester 2020 |
Name | Herr Dr. Mohsen Ghaffari |
Lehrgebiet | Informatik |
ghaffari@inf.ethz.ch | |
URL | https://people.inf.ethz.ch/gmohsen/ |
Departement | Informatik |
Beziehung | Assistenzprofessor (Tenure Track) |
Nummer | Titel | ECTS | Umfang | Dozierende | |
---|---|---|---|---|---|
252-0209-00L | Algorithms, Probability, and Computing | 8 KP | 4V + 2U + 1A | B. Gärtner, M. Ghaffari, R. Kyng, D. Steurer | |
Kurzbeschreibung | Advanced 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). | ||||
Lernziel | Studying and understanding of fundamental advanced concepts in algorithms, data structures and complexity theory. | ||||
Skript | Will be handed out. | ||||
Literatur | Introduction 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. | ||||
252-4202-00L | Seminar in Theoretical Computer Science | 2 KP | 2S | E. Welzl, B. Gärtner, M. Ghaffari, M. Hoffmann, J. Lengler, D. Steurer, B. Sudakov | |
Kurzbeschreibung | Präsentation wichtiger und aktueller Arbeiten aus der theoretischen Informatik, sowie eigener Ergebnisse von Diplomanden und Doktoranden. | ||||
Lernziel | Das Lernziel ist, Studierende an die aktuelle Forschung heranzuführen und sie in die Lage zu versetzen, wissenschaftliche Arbeiten zu lesen, zu verstehen, und zu präsentieren. | ||||
Voraussetzungen / Besonderes | This 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. | ||||
263-4500-00L | Advanced Algorithms | 9 KP | 3V + 2U + 3A | M. Ghaffari | |
Kurzbeschreibung | This is a graduate-level course on algorithm design (and analysis). It covers a range of topics and techniques in approximation algorithms, sketching and streaming algorithms, and online algorithms. | ||||
Lernziel | This course familiarizes the students with some of the main tools and techniques in modern subareas of algorithm design. | ||||
Inhalt | The lectures will cover a range of topics, tentatively including the following: graph sparsifications while preserving cuts or distances, various approximation algorithms techniques and concepts, metric embeddings and probabilistic tree embeddings, online algorithms, multiplicative weight updates, streaming algorithms, sketching algorithms, and derandomization. | ||||
Skript | https://people.inf.ethz.ch/gmohsen/AA20/ | ||||
Voraussetzungen / Besonderes | This course is designed for masters and doctoral students and it especially targets those interested in theoretical computer science, but it should also be accessible to last-year bachelor students. Sufficient comfort with both (A) Algorithm Design & Analysis and (B) Probability & Concentrations. E.g., having passed the course Algorithms, Probability, and Computing (APC) is highly recommended, though not required formally. If you are not sure whether you're ready for this class or not, please consult the instructor. |