Peter Widmayer: Catalogue data in Spring Semester 2014

Award: The Golden Owl
Name Prof. em. Dr. Peter Widmayer
FieldInformatik
Address
Inst. f. Theoretische Informatik
ETH Zürich, CAB H 39.2
Universitätstrasse 6
8092 Zürich
SWITZERLAND
E-mailwidmayer@inf.ethz.ch
DepartmentComputer Science
RelationshipProfessor emeritus

NumberTitleECTSHoursLecturers
252-0002-AALData Structures and Algorithms Restricted registration - show details
Enrolment only for MSc students who need this course as additional requirement.
7 credits15RP. Widmayer
AbstractThis course is about fundamental algorithm design paradigms (such as induction, divide-and-conquer, backtracking, dynamic programming), classic algorithmic problems (such as sorting and searching), and data structures (such as lists, hashing, search trees). The connection between algorithms and data structures is explained for geometric and graph problems.
Learning objectiveAn understanding of the design and analysis of fundamental algorithms and data structures.
Prerequisites / NoticeThis is a self-study course. The relevant topics are those of the underlying course taught in the previous spring semester. A course summary with literature in English is provided at:

http://www.cadmo.ethz.ch/education/lectures/FS12/DA/
252-0002-00LData Structures and Algorithms Information 7 credits4V + 2UP. Widmayer
AbstractThis course is about fundamental algorithm design paradigms (such as induction, divide-and-conquer, backtracking, dynamic programming), classic algorithmic problems (such as sorting and searching), and data structures (such as lists, hashing, search trees). The connection between algorithms and data structures is explained for geometric and graph problems.
Learning objectiveAn understanding of the design and analysis of fundamental algorithms and data structures.
ContentEs werden grundlegende Algorithmen und Datenstrukturen vorgestellt und analysiert. Dazu gehören auf der einen Seite Entwurfsmuster für Algorithmen, wie Induktion, divide-and-conquer, backtracking und dynamische Optimierung, ebenso wie klassische algorithmische Probleme, wie Suchen und Sortieren. Auf der anderen Seite werden Datenstrukturen für verschiedene Zwecke behandelt, darunter verkettete Listen, Hashtabellen, balancierte Suchbäume, verschiedene heaps und union-find-Strukturen. Weiterhin wird Adaptivität bei Datenstrukturen (wie etwa Splay-Bäume) und bei Algorithmen (wie etwa online-Algorithmen) beleuchtet. Das Zusammenspiel von Algorithmen und Datenstrukturen wird anhand von Geometrie- und Graphenproblemen illustriert.
LiteratureTh. Ottmann, P.Widmayer: Algorithmen und Datenstrukturen, Spektrum-Verlag, 5. Auflage, Heidelberg, Berlin, Oxford, 2011
Prerequisites / NoticeVoraussetzung:
252-0021-00L Einführung in die Programmierung
252-0934-00LAlgorithms and Complexity (FS) Information 1 credit1SP. Widmayer, J. Hromkovic
AbstractThis seminar treats selected problems of current interest in the area of algorithms and complexity.
Learning objectiveDevelop an understanding of selected problems of current interest in the area of algorithms and complexity.
ContentThis seminar treats selected problems of current interest in the area of algorithms and complexity.
Lecture notesNone.
LiteratureResearch papers, to be chosen in the seminar.
Prerequisites / NoticePrerequisites: Basic understanding of algorithms and complexity.
252-3002-00LAlgorithms for Database Systems Information 2 credits2SP. Widmayer, D. Kossmann
AbstractQuery processing, optimization, stream-based systems, distributed and parallel databases, non-standard databases.
Learning objectiveDevelop an understanding of selected problems of current interest in the area of algorithms for database systems.
252-4220-00LA Taste of Research: Algorithms and Combinatorics Information 2 credits2SB. Gärtner, J. Matousek, A. Steger, E. Welzl, P. Widmayer
AbstractStudents work together with lecturers on open problems in algorithms and combinatorics.
Learning objectiveThe goal is to learn and practice important research techniques: literature search, understanding and presenting research papers, developing ideas in the group, testing of conjectures with the computer, writing down results.
ContentWork on original research papers and open problems in the areas of algorithms and combinatorics.
Lecture notesNot available.
LiteratureWill be announced in the seminar and on the seminar's web page.
Prerequisites / NoticePassed first-year exam.
252-4302-00LSeminar Algorithmic Game Theory Information 2 credits2SP. Widmayer, M. Mihalak
AbstractIn the seminar we will get familiar with the current original research in the area of algorithmic game theory by reading and presenting selected research papers in that area.
Learning objectiveDevelop an understanding of selected problems of current interest in the area of algorithmic game theory, and a practice of a scientific presentation.
ContentStudy and understanding of selected topics of current interest in algorithmic game theory such as: Complexity Results (class PPAD, PLS, NP), Sponsored Search, Approximation Algorithms via Algorithmic Game Theory, Price of Anarchy, New paradigms of computation (e.g., envy-fee, truthful), Mechanism Design.
LiteratureSelected research articles.
Prerequisites / NoticeYou must have passed our "Algorithmic Game Theory" class (or have acquired equivalent knowledge, in exceptional cases).