CORDIS Project
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This project focuses on the study of multiple random walks to improve algorithms for complex networks. It aims to develop new metrics and insights that can enhance the efficiency of algorithms used in various applications, such as routing and clustering.
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,…
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