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On Dynamic Network Models and Application to Causal Impact:
, In:
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
,
Chen, Yu-Chia
;
Bijral, Avleen S.
;
Ferres, Juan Lavista
- p. 1194-1204 , 2019
Link:
https://dl.acm.org/doi/10.1145/3292500.3330990
RT T1 <cTitle>Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining</cTitle>: T1 <Title>On Dynamic Network Models and Application to Causal Impact</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3330990&Exemplar=1&LAN=DE A1 Chen, Yu-Chia A1 Bijral, Avleen S. A1 Ferres, Juan Lavista PB ACM YR 2019 K1 causal impact K1 clustering K1 dynamic networks K1 stochastic block model K1 Computing methodologies K1 Machine learning K1 Learning paradigms K1 Unsupervised learning K1 Machine learning approaches K1 Learning in probabilistic graphical models K1 Maximum a posteriori modeling K1 Mathematics of computing K1 Probability and statistics K1 Stochastic processes SP 1194 OP 1204 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3292500.3330990 DO https://dl.acm.org/doi/10.1145/3292500.3330990 SF ELIB - SuUB Bremen
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