Universität Wien FIND

Return to Vienna for the summer semester of 2022. We are planning to hold courses mainly on site to enable the personal exchange between you, your teachers and fellow students. We have labelled digital and mixed courses in u:find accordingly.

Due to COVID-19, there might be changes at short notice (e.g. individual classes in a digital format). Obtain information about the current status on u:find and check your e-mails regularly.

Please read the information on https://studieren.univie.ac.at/en/info.

040968 UK Graph Algorithms and Network Flows (2011S)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 30 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

Tuesday 01.03. 16:30 - 18:00 Leopold-Schmetterer-Seminarraum, Universitätsstraße 5, 3.Stock
Tuesday 08.03. 16:30 - 18:00 Leopold-Schmetterer-Seminarraum, Universitätsstraße 5, 3.Stock
Tuesday 15.03. 16:30 - 18:00 Leopold-Schmetterer-Seminarraum, Universitätsstraße 5, 3.Stock
Tuesday 22.03. 16:30 - 18:00 Leopold-Schmetterer-Seminarraum, Universitätsstraße 5, 3.Stock
Tuesday 29.03. 16:30 - 18:00 Leopold-Schmetterer-Seminarraum, Universitätsstraße 5, 3.Stock
Tuesday 05.04. 16:30 - 18:00 Leopold-Schmetterer-Seminarraum, Universitätsstraße 5, 3.Stock
Tuesday 12.04. 16:30 - 18:00 Leopold-Schmetterer-Seminarraum, Universitätsstraße 5, 3.Stock
Tuesday 03.05. 16:30 - 18:00 Leopold-Schmetterer-Seminarraum, Universitätsstraße 5, 3.Stock
Tuesday 10.05. 16:30 - 18:00 Leopold-Schmetterer-Seminarraum, Universitätsstraße 5, 3.Stock
Tuesday 17.05. 16:30 - 18:00 Leopold-Schmetterer-Seminarraum, Universitätsstraße 5, 3.Stock
Tuesday 24.05. 16:30 - 18:00 Leopold-Schmetterer-Seminarraum, Universitätsstraße 5, 3.Stock
Tuesday 31.05. 16:30 - 18:00 Leopold-Schmetterer-Seminarraum, Universitätsstraße 5, 3.Stock
Tuesday 07.06. 16:30 - 18:00 Leopold-Schmetterer-Seminarraum, Universitätsstraße 5, 3.Stock
Tuesday 21.06. 16:30 - 18:00 Leopold-Schmetterer-Seminarraum, Universitätsstraße 5, 3.Stock
Tuesday 28.06. 16:30 - 18:00 Leopold-Schmetterer-Seminarraum, Universitätsstraße 5, 3.Stock

Information

Aims, contents and method of the course

In this course, we are going to study two main aspects of networks:

1) Design of some optimal network topologies. We will study several representative problems from this well-established research field using methods of complexity, algorithms and operations research.

2) Analysis of social networks. The growing public excitement by the global ``connectivity'' of the modern society has motivated scientists from multiple scientific disciplines (computer science, applied mathematics, economy and sociology) to develop this new interdisciplinary research field. We will study several graph-theoretical concept of social networks, their complexity and algorithmic approaches for their analysis.

Assessment and permitted materials

- Homework (25%)
- Presentation of a selected topic (15%)
- Oral exam (60%)

At least 60% in total are needed to pass the exam.

Minimum requirements and assessment criteria

This course should help graduate students to:

a) understand information about networks, and
b) develop models and algorithms to design, manage and analyse networks.

Examination topics


1) Graphs.
- Graph Traversal Algorithms. Topological Ordering.
- Dynamic Programming. Shortest Path Algorithms.
- Greedy Algorithms. Minimum Spanning Tree.
- Flow Algorithms.

2) Analysis of social networks
- Graph partitioning (strong and week ties, betweenness measures)
- Networks in their surrounding contexts: homophily, affiliation
- Positive and negative relationships: structural balance, weaker form of structural balance, generalization
- Cascading behavior in networks: diffusion, cascades and clusters. Knowledge, threshold and collective action. The cascade capacity.
- Spreading epidemics in networks: branching process, SIR vs. SIS epidemic model. Analysis of branching process.

Reading list

* Network Flows: Theory, Algorithms, and Applications, by Ravindra K. Ahuja, Thomas L. Magnanti, James B. Orlin
* Algorithm Design, by Eva Tardos, Jon Kleinberg
* Networks, Crowds, and Markets: Reasoning About a Highly Connected World, by David Easley and
Jon Kleinberg
http://www.cs.cornell.edu/home/kleinber/networks-book/

Association in the course directory

Last modified: Mo 07.09.2020 15:29