Explore the words cloud of the DYNAMICMARCH project. It provides you a very rough idea of what is the project "DYNAMICMARCH" about.
The following table provides information about the project.
Coordinator |
THE CHANCELLOR MASTERS AND SCHOLARSOF THE UNIVERSITY OF CAMBRIDGE
Organization address contact info |
Coordinator Country | United Kingdom [UK] |
Total cost | 1˙400˙789 € |
EC max contribution | 1˙400˙789 € (100%) |
Programme |
1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC)) |
Code Call | ERC-2015-STG |
Funding Scheme | ERC-STG |
Starting year | 2016 |
Duration (year-month-day) | from 2016-05-01 to 2021-04-30 |
Take a look of project's partnership.
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1 | THE CHANCELLOR MASTERS AND SCHOLARSOF THE UNIVERSITY OF CAMBRIDGE | UK (CAMBRIDGE) | coordinator | 1˙400˙789.00 |
Markov chains are fundamental processes and have been studied in nearly every scientific discipline in the past 100 years. In computer science, reversible Markov chains, also known as random walks, form the basis of many efficient randomised algorithms which have been successfully applied to a variety of complex sampling, learning and optimisation problems.
Nowadays an increasing number of algorithms and processes on networks are based on multiple (concurrent and possibly dependent) random walks, including algorithms for packet routing, content search, graph clustering, link prediction and website ranking. This trend will be reinforced by the steady growth of large-scale networks and massive data sets. However, the existing theory of single random walks is not well-suited to cope with the complexity inherent to multiple random walks, and even for independent walks many fundamental questions remain open.
The goal of this proposal is to develop a systematic and rigorous study of multiple random walks. First, we will analyse this random process via commonly used metrics such as hitting times, cover times, mixing times as well as new quantities which are unique to multiple random walks. Then we will connect these quantities to structural properties of the underlying graph. Finally, these insights will be applied to the design of new efficient randomised algorithms for large graphs and distributed networks.
year | authors and title | journal | last update |
---|---|---|---|
2019 |
Varun Kanade, Frederik-Mallmann-Trenn, Thomas Sauerwald On coalescence time in graphs: When is coalescing as fast as meeting?: Extended Abstract published pages: , ISSN: , DOI: |
Proceedings of the 30th Annual ACM-SIAM Symposium on Discrete Algorithms | 2020-01-20 |
2019 |
Nicolas Rivera, Thomas Sauerwald, Alexandre Stauffer, John Sylvester The dispersion time of random walks on finite graphs published pages: , ISSN: , DOI: |
Proceedings of the 31st ACM Symposium on Parallelism in Algorithms and Architectures | 2020-01-20 |
2017 |
Leran Cai, Thomas Sauerwald Randomized Load Balancing on Networks with Stochastic Inputs published pages: 139:1--139:14, ISSN: , DOI: |
Proceedings of the 44th International Colloquium on Automata, Languages, and Programming (ICALP) | 2020-01-20 |
2017 |
Thomas Sauerwald Multiple Random Walks published pages: 60-61, ISSN: 1868-8969, DOI: |
Science & Technology 24 | 2020-01-20 |
2017 |
Andrej Ivaskovic, Adrian Kosowski, Dominik Pajak, Thomas Sauerwald Multiple Random Walks on Paths and Grids published pages: 44:1--44:14, ISSN: 1868-8969, DOI: 10.4230/LIPIcs.STACS.2017.44 |
34th Symposium on Theoretical Aspects of Computer Science (STACS 2017) 66 | 2020-01-20 |
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The information about "DYNAMICMARCH" are provided by the European Opendata Portal: CORDIS opendata.
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