SMRI Seminar: Elvira -- State-space models as graphs

SMRI Seminar: ’State-space models as graphs’ 
Victor Elvira (University of Edinburgh) 

Date and time: Thursday 29 February, 13:00-14:00 AEDT 
Location: Law Annex Lecture Theatre 026 and online 
Register/join for online attendance: https://uni-sydney.zoom.us/j/82234629371 

Abstract: Modeling and inference in multivariate time series is central in statistics,
signal processing, and machine learning.  A fundamental question when analyzing
multivariate sequences is the search for relationships between their entries (or the
modeled hidden states), especially when the inherent structure is a directed (causal)
graph.  In such context, graphical modeling combined with sparsity constraints allows to
limit the proliferation of parameters and enables a compact data representation which is
easier to interpret in applications, e.g., in inferring causal relationships of physical
processes in a Granger sense.  In this talk, we present a novel perspective consisting
on state-space models being interpreted as graphs.  Then, we propose novel algorithms
that exploit this new perspective for the estimation of the linear matrix operator and
also the covariance matrix in the state equation of a linear-Gaussian state-space
model.  Finally, we discuss the extension of this perspective for the estimation of
other model parameters in more complicated models.  

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Please join us after the seminar for SMRI afternoon tea, 2:00-2:45pm every Thursday on
the SMRI Terrace (accessed through A14-04-L4.36) 

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Current and past seminar info (including recordings) can be found on the seminars
webpage.  

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