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UID:20250714T211342EDT-2889u9urhC@132.216.98.100
DTSTAMP:20250715T011342Z
DESCRIPTION:Title: Persistence and root detection algorithms in growing net
 works\n\nAbstract: Motivated by questions in Network Archaeology\, we inve
 stigate statistics of dynamic networks that are persistent\, that is\, the
 y fixate almost surely after some random time as the network grows. We con
 sider generalized attachment models of network growth where at each time n
 \, an incoming vertex attaches itself to the network through m n edges att
 ached one-by-one to existing vertices with probability proportional to an 
 arbitrary function f of their degree. We identify the class of attachment 
 functions f for which the maximal degree vertex persists and obtain asympt
 otics for its index when it does not. We also show that for tree networks\
 , the centroid of the tree persists and use it to device polynomial time r
 oot finding algorithms and quantify their efficacy. Our methods rely on an
  interplay between dynamic random networks and their continuous time embed
 dings.\n\nThis is joint work with Shankar Bhamidi.\n\nLink: https://mcgill
 .zoom.us/j/97093259428?pwd=d25yR0J6WGViSzFZOE5rT01YZnBJQT09\n\nMeeting ID:
  970 9325 9428\n\nPasscode: problab\n
DTSTART:20201021T150000Z
DTEND:20201021T160000Z
SUMMARY:Sayan Banerjee (UNC)
URL:/mathstat/channels/event/sayan-banerjee-unc-325388
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