Learning latent variable dynamic graphical models by confidence sets selection
V Ciccone, A Ferrante, M Zorzi - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
We consider the problem of learning dynamic latent variable graphical models. More
precisely, given an estimate of the graphical model based on a finite data sample, we …
precisely, given an estimate of the graphical model based on a finite data sample, we …
On the Existence of a Solution to a Spectral Estimation Problem à la Byrnes–Georgiou–Lindquist
A parametric spectral estimation problem in the style of Byrnes, Georgiou, and Lindquist was
posed in [1], but the existence of a solution was only proved in a special case. Based on …
posed in [1], but the existence of a solution was only proved in a special case. Based on …
A scalable strategy for the identification of latent-variable graphical models
In this article, we propose an identification method for latent-variable graphical models
associated with autoregressive (AR) Gaussian stationary processes. The identification …
associated with autoregressive (AR) Gaussian stationary processes. The identification …
On the well-posedness of a parametric spectral estimation problem and its numerical solution
B Zhu - IEEE Transactions on Automatic Control, 2019 - ieeexplore.ieee.org
This paper concerns a spectral estimation problem in which we want to find a spectral
density function that is consistent with estimated second-order statistics. It is an inverse …
density function that is consistent with estimated second-order statistics. It is an inverse …
Gramian optimization with input-power constraints
G Baggio, S Zampieri… - 2019 IEEE 58th …, 2019 - ieeexplore.ieee.org
The optimization of the controllability Gramian of a given linear continuous-time system via
proper design of its input matrix is a rather unexplored problem in the control literature. The …
proper design of its input matrix is a rather unexplored problem in the control literature. The …
Line Spectral Analysis Using the G-Filter: An Atomic Norm Minimization Approach
B Zhu - arXiv preprint arXiv:2410.12358, 2024 - arxiv.org
The area of spectral analysis has a traditional dichotomy between continuous spectra
(spectral densities) which correspond to purely nondeterministic processes, and line spectra …
(spectral densities) which correspond to purely nondeterministic processes, and line spectra …
A fast robust numerical continuation solver to a two‐dimensional spectral estimation problem
B Zhu, J Liu - IET Control Theory & Applications, 2022 - Wiley Online Library
This paper presents a fast algorithm to solve a spectral estimation problem for two‐
dimensional random fields. The latter is formulated as a convex optimization problem with …
dimensional random fields. The latter is formulated as a convex optimization problem with …
Graphical model selection for a particular class of continuous-time processes
M Zorzi - Kybernetika, 2019 - dml.cz
Graphical models provide an undirected graph representation of relations between the
components of a random vector. In the Gaussian case such an undirected graph is used to …
components of a random vector. In the Gaussian case such an undirected graph is used to …
Link prediction: A graphical model approach
We consider the problem of link prediction in networks whose edge structure may vary
(sufficiently slowly) over time. This problem, with applications in many important areas …
(sufficiently slowly) over time. This problem, with applications in many important areas …
Space and spectral domain relative entropy for homogeneous random fields
V Ciccone, A Ferrante - Automatica, 2020 - Elsevier
A classical result in spectral estimation establishes that the relative entropy rate between two
zero-mean stationary Gaussian processes can be computed explicitly in terms of their …
zero-mean stationary Gaussian processes can be computed explicitly in terms of their …