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SUMMARY:Efficient edge-centrality measures based on matrix functions of th
 e line graph
DTSTART:20260428T090000Z
DTEND:20260428T220000Z
DTSTAMP:20260416T081000Z
UID:indico-event-341@events.dm.unipi.it
DESCRIPTION:Speakers: Francesco Zigliotto\n\nWhile network centrality is p
 redominantly studied from a node perspective\, here we investigate edge-ce
 ntrality measures based on matrix functions. Specifically\, we examine cen
 trality within the context of the line graph\, a structure where the roles
  of nodes and edges are inverted. Although any standard node-centrality me
 tric can theoretically be applied to a line graph to assess edge importanc
 e\, line graphs generally possess significantly more nodes than their orig
 inal counterparts\, which makes computing matrix functions of their adjace
 ncy matrices computationally infeasible. To address this bottleneck\, we i
 ntroduce novel matrix function identities that reduce the dimensionality o
 f the required calculations. By operating on matrices of a much smaller si
 ze\, these identities yield edge-centrality algorithms that are\, in pract
 ice\, nearly as fast as their node-level equivalents. Both directed and un
 directed graphs are treated.\n\nhttps://events.dm.unipi.it/event/341/
LOCATION:Aula Magna (Dipartimento di Matematica)
URL:https://events.dm.unipi.it/event/341/
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