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Network Inference via the Time-Varying Graphical Lasso
[article]
2017
arXiv
pre-print
Many important problems can be modeled as a system of interconnected entities, where each entity is recording time-dependent observations or measurements. In order to spot trends, detect anomalies, and interpret the temporal dynamics of such data, it is essential to understand the relationships between the different entities and how these relationships evolve over time. In this paper, we introduce the time-varying graphical lasso (TVGL), a method of inferring time-varying networks from raw time
arXiv:1703.01958v2
fatcat:hlilnu62xrcgpgt2qgxyiuacve