The Mystery Behind Large Graphs
Our guest in this episode is David Tench, a Grace Hopper postdoctoral fellow at Lawrence Berkeley National Labs, who specializes in scalable graph algorithms and compression techniques to tackle massive datasets.
In this episode, we will learn how his techniques enable real-time analysis of large datasets, such as particle tracking in physics experiments or social network analysis, by reducing storage requirements while preserving critical structural properties.
David also challenges the common belief that giant graphs are sparse by pointing to a potential bias: Maybe because of the…
The skinny
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