Algorithmics: Theory and Practice

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Sidebar Home. Teaching SoSe Algorithmic Game Theory and the Internet.

Seminar Advanced Algorithms Blum. Seminar Advanced Algorithms Kesselheim. Projektgruppe Entwurf und Implementierung von Algorithmen. Lab Combinatorial Algorithms. Some more notes regarding the exam Getting to know concepts is an important learning objective.

Algorithmics: Theory and Practice

When Where Start Lecturer Thursday, 2. In this course, we will introduce you to the foundations of algorithmic game theory, including basic game theory,. Lecture Notes Apr 9, Congestion Games.

Lecture Notes Apr 27, Correlated Equilibria. Lecture Notes May 04, Price of Anarchy. Lecture Notes Jun 11, Smooth Mechanisms.

Bridging the Gap Between Algorithm Theory and Practice

Lecture Notes Jun 18, Walrasian Equilibria. Lecture Notes Jun 25, Revenue Maximization.

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Lecture Notes Jul 02, Allocations without Money. Lecture Notes Jul 06, Stable Matching.

Discrete mathematics II : Algorithms and complexity

Lecture Notes Jul 16, Cake Cutting. Lecture Notes Jul 20, Cost Sharing. Exercise Set 1, due Apr 16, Exercise Set 2, due Apr 23, Silvio Lattanzi , Google Research Zurich. His main research interests are in algorithms, large-scale graph mining, information retrieval and machine learning. He has published more than 40 papers in top tier conferences and journals in information retrieval, machine learning and algorithms. He has been awarded of KDD best paper award.

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Previously, he has presented tutorials at WSDM conference. He currently serves as a tech lead for the large-scale graph mining project at Google, and he is currently leading a new algorithm and optimization research group in Google Zurich.

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He received a B. This course assumes a sufficient mathematical maturity, equivalent to the level of a third year student in engineering.

The course is an introduction to algorithmics, treating mainly of non-numerical aspects. A mathematical analysis of the existence and complexity of algorithms for classic problems pertaining to discrete structures and problems.

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Previous exposition to non-elementary algorithmic questions is useful to the student; other than that, no prerequisite in algorithmics is assumed. Introduction to the basic algorithms for sorting and the efficient implementation of different data structures including an analysis of worst case and average case complexity.

  • MA-INF Algorithmic Game Theory and the Internet [Informatik-Abteilung V]!
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  • Treatment of important algorithm classes including greedy and dynamic programming algorithms. Aspects of complexity theory including NP-completeness, complexity classes and decidability. The course is organised in lessons and weekly homework, for which non-compulsory consulting is offered. The students are evaluated through an individual written exam, on the objectives listed above.