Probabilistic design of optimal sequential decision-making algorithms in learning and control
This survey is focused on certain sequential decision-making problems that involve
optimizing over probability functions. We discuss the relevance of these problems for …
optimizing over probability functions. We discuss the relevance of these problems for …
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 …
Autoregressive identification of Kronecker graphical models
M Zorzi - Automatica, 2020 - Elsevier
We address the problem to estimate a Kronecker graphical model corresponding to an
autoregressive Gaussian stochastic process. The latter is completely described by the power …
autoregressive Gaussian stochastic process. The latter is completely described by the power …
On the statistical consistency of a generalized cepstral estimator
We consider the problem to estimate the generalized cepstral coefficients of a stationary
stochastic process or stationary multidimensional random field. It turns out that a naive …
stochastic process or stationary multidimensional random field. It turns out that a naive …
Fusion of sensors data in automotive radar systems: A spectral estimation approach
B Zhu, A Ferrante, J Karlsson… - 2019 IEEE 58th …, 2019 - ieeexplore.ieee.org
To accurately estimate locations and velocities of surrounding targets (cars) is crucial for
advanced driver assistance systems based on radar sensors. In this paper we derive …
advanced driver assistance systems based on radar sensors. In this paper we derive …
M2-spectral estimation: A relative entropy approach
This paper deals with M 2-signals, namely multivariate (or vector-valued) signals defined
over a multidimensional domain. In particular, we propose an optimization technique to …
over a multidimensional domain. In particular, we propose an optimization technique to …
A well-posed multidimensional rational covariance and generalized cepstral extension problem
In the present paper we consider the problem of estimating the multidimensional power
spectral density which describes a second-order stationary random field from a finite number …
spectral density which describes a second-order stationary random field from a finite number …
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 a probabilistic approach to synthesize control policies from example datasets
D Gagliardi, G Russo - Automatica, 2022 - Elsevier
This paper is concerned with the design of control policies from example datasets. The case
considered is when just a black box description of the system to be controlled is available …
considered is when just a black box description of the system to be controlled is available …
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 …