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Multivariate Time Series Synthesis Using Generative Adversa..:

, In: Proceedings of the ACM/SPEC International Conference on Performance Engineering,

Leznik, Mark ; Michalsky, Patrick ; Willis, Peter... - p. 43-50 , 2021

Link: https://dl.acm.org/doi/10.1145/3427921.3450257

RT 
T1 <cTitle>Proceedings of the ACM/SPEC International Conference on Performance Engineering</cTitle>: T1 <Title>Multivariate Time Series Synthesis Using Generative Adversarial Networks</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3450257&Exemplar=1&LAN=DE
				
A1 Leznik, Mark
A1 Michalsky, Patrick
A1 Willis, Peter
A1 Schanzel, Benjamin
A1 Östberg, Per-Olov
A1 Domaschka, Jörg
PB ACM
YR 2021
K1 generative adversarial networks
K1 server workload
K1 synthetic data
K1 time series synthesis
K1 workload generation
K1 Computing methodologies
K1 Machine learning
K1 Machine learning approaches
K1 Neural networks
K1 Networks
K1 Network algorithms
K1 Control path algorithms
K1 Traffic engineering algorithms
K1 Network performance evaluation
K1 Network simulations
K1 Network measurement
K1 Mathematics of computing
K1 Discrete mathematics
K1 Graph theory
K1 Network flows
SP 43
OP 50
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3427921.3450257
DO https://dl.acm.org/doi/10.1145/3427921.3450257
SF ELIB - SuUB Bremen

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