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Learning Graphs from Noisy Epidemic Cascades:

, In: Abstracts of the 2019 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems,

Hoffmann, Jessica H. ; Caramanis, Constantine - p. 3-4 , 2019

Link: https://dl.acm.org/doi/10.1145/3309697.3331511

RT 
T1 <cTitle>Abstracts of the 2019 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems</cTitle>: T1 <Title>Learning Graphs from Noisy Epidemic Cascades</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3331511&Exemplar=1&LAN=DE
				
A1 Hoffmann, Jessica H.
A1 Caramanis, Constantine
PB ACM
YR 2019
K1 contact process on graph
K1 epidemics
K1 graph reconstruction
K1 noisy inverse problem
K1 robust graph algorithms
K1 sir model
K1 Mathematics of computing
K1 Discrete mathematics
K1 Graph theory
K1 Graph algorithms
K1 Probability and statistics
K1 Probabilistic inference problems
K1 Computing most probable explanation
K1 Probabilistic reasoning algorithms
K1 Networks
K1 Network algorithms
K1 Theory of computation
K1 Design and analysis of algorithms
K1 Graph algorithms analysis
K1 Network properties
K1 Network dynamics
K1 Theory and algorithms for application domains
K1 Machine learning theory
K1 Sample complexity and generalization bounds
K1 Information systems
K1 World Wide Web
K1 Web applications
K1 Social networks
K1 Combinatorics
K1 Algorithmic game theory and mechanism design
K1 Randomness, geometry and discrete structures
K1 Random walks and Markov chains
SP 3
OP 4
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3309697.3331511
DO https://dl.acm.org/doi/10.1145/3309697.3331511
SF ELIB - SuUB Bremen

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