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Core Decomposition of Uncertain Graphs
Published on Feb 4, 20253566 Views
Core decomposition has proven to be a useful primitive for a wide range of graph analyses. One of its most appealing features is that, unlike other notions of dense subgraphs, it can be computed linea
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Presentation
Core Decomposition of Uncertain Graphs00:00
Introduction - 100:09
Introduction - 200:19
Dense subgraphs - 100:23
Dense subgraphs - 200:37
Dense subgraphs - 300:49
k-core decomposition - 101:01
k-core decomposition - 201:16
k-core decomposition - 301:37
k-core decomposition - 401:54
k-core decomposition - 502:05
k-core decomposition - 602:13
k-core decomposition - 702:28
Introduction - 303:04
Uncertain graphs - 103:14
Uncertain graphs - 204:09
Uncertain graphs - 304:36
Uncertain graphs - 404:42
Uncertain graphs - 505:16
Uncertain graphs - 605:25
Introduction - 405:51
Introduction - 506:05
Complications - 106:15
Complications - 206:33
Complications - 306:37
Complications - 406:40
Probabilistic (k,η)-cores - 106:57
Probabilistic (k,η)-cores - 207:52
Probabilistic (k,η)-cores - 308:24
Probabilistic (k,η)-cores - 408:54
Probabilistic (k,η)-cores - 509:13
Probabilistic (k,η)-cores - 609:30
Computing probabilistic cores - 110:07
Computing probabilistic cores - 210:35
Computing probabilistic cores - 310:58
Computing probabilistic cores - 411:31
Applications12:05
1. Task-driven team formation problem - 112:31
1. Task-driven team formation problem - 212:50
1. Task-driven team formation problem - 313:05
2. Influence-maximization problem - 113:29
2. Influence-maximization problem - 213:57
2. Influence-maximization problem - 314:01
2. Influence-maximization problem - 414:08
2. Influence-maximization problem - 514:14
2. Influence-maximization problem - 614:34
2. Influence-maximization problem - 714:53
2. Influence-maximization problem - 815:13
Influence-maximization experiment - 115:33
Influence-maximization experiment - 215:55
Conclusions - 116:02
Conclusions - 216:12
Conclusions - 316:23
Conclusions - 416:38
Questions?16:48