CORDIS Project
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This project investigates how different types of metric spaces can be efficiently represented in low-dimensional Euclidean space. By exploring metric embedding techniques, the research aims to improve algorithms for analyzing large datasets in fields such as computational biology and text mining.
We are currently witnessing the generation of massive amounts of data that require analysis, particularly in application areas such as computational biology, text mining, networking and web applications.
Many of these computational tasks can be performed efficiently in low dimensional Euclidean space.
In this research proposal, I will set out to investigate fundamental questions in the field of metric embedding, which could provide tools and algorithms for handling arbitrary metric data.
The di…
BEN-GURION UNIVERSITY OF THE NEGEV
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