We review the state of the art of clustering financial time series and the study of their
correlations alongside other interaction networks. The aim of the review is to gather in one …

Determining interrelatedness structure of various entities from multiple time series data is of
significant interest to many areas. Knowledge of such a structure can aid in identifying cause …

We address the problem of identifying the topology of an unknown weighted, directed
network of LTI systems stimulated by wide-sense stationary noises of unknown power …

The paper tackles the problem of identifying an individual transfer function in a network of
linear dynamical systems in the presence of loops under the assumptions that (i) only a …

We propose a mathematical framework, based on conic geometric programming, to control a
susceptible-infected-susceptible viral spreading process taking place in a directed contact …

In this article, the optimal sample complexity of learning the underlying interactions or
dependencies of a Linear Dynamical System (LDS) over a Directed Acyclic Graph (DAG) is …

In many applications, it is of interest to derive information about the topology and the internal
connections of multiple dynamical systems interacting together. Examples can be found in …

We present and analyze a novel regularization technique based on enhancing our dataset
with corrupted copies of our original data. The motivation is that since the learning algorithm …

In this dissertation we take a graph-theoretic approach to address different aspects of
identification of dynamic networks. We consider a class of networks where each node is …

This paper addresses the problem of identifying the topology of an unknown, weighted,
directed network running a consensus dynamics. We propose a methodology to reconstruct …