CORDIS Project
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This project investigates graph algorithms under conditions of uncertainty, where complete data knowledge is not guaranteed. It explores the use of randomization and derandomization techniques to enhance algorithm performance in dynamic and distributed environments.
Much of the research on the foundations of graph algorithms is carried out under the assumption that the algorithm has full knowledge of the input data.In spite of the theoretical appeal and simplicity of this setting, the assumption that
the algorithm has full knowledge does not always hold.Indeed uncertainty and partial knowledge arise in many settings.One example is where the data is very large, in which case even reading the entire data once is infeasible, and sampling
is required.Another ex…
TEL AVIV UNIVERSITY
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