Dynamic Regret Analysis for Online Tracking of Time-varying Structural Equation Model Topologies
Identifying dependencies among variables in a complex system is an important problem in network science. Structural equation models (SEM) have been used widely in many fields for topology inference, because they are tractable and incorporate exogenous influences in the model. Topology identification...
Gespeichert in:
Hauptverfasser: | , , |
---|---|
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | Identifying dependencies among variables in a complex system is an important
problem in network science. Structural equation models (SEM) have been used
widely in many fields for topology inference, because they are tractable and
incorporate exogenous influences in the model. Topology identification based on
static SEM is useful in stationary environments; however, in many applications
a time-varying underlying topology is sought. This paper presents an online
algorithm to track sparse time-varying topologies in dynamic environments and
most importantly, performs a detailed analysis on the performance guarantees.
The tracking capability is characterized in terms of a bound on the dynamic
regret of the proposed algorithm. Numerical tests show that the proposed
algorithm can track changes under different models of time-varying topologies. |
---|---|
DOI: | 10.48550/arxiv.2003.08145 |