activity
20202023
most citedModeling of Low Rank Time Series

2 citations · 5 across the 7 of their papers we have counts for

collaborators

8 papers

stat.ML2023★ 1 cited

Dealing with Collinearity in Large-Scale Linear System Identification Using Gaussian Regression

Wenqi Cao, Gianluigi Pillonetto

Many problems arising in control require the determination of a mathematical model of the application. This has often to be performed starting from input-output data, leading to a…

math.AG2022

Spectral Factorization of Rank-Deficient Rational Densities

Wenqi Cao, Anders Lindquist

Though there have been hundreds of methods on solving rational spectral factorization, most of them are based on a positive definite density matrix assumption. In this work, we pro…

cs.DC2022★ 1 cited

A Smart Contract based Crowdfunding Mechanism for Hierarchical Federated Learning

Hongze Liu, Jie Li, Shijing Yuan +2

Hierarchical Federated Learning (HFL) is introduced as a promising technique that allows model owners to fully exploit computational resources and bandwidth resources to train the…

math.DS2022

Dealing with collinearity in large-scale linear system identification using Bayesian regularization

Wenqi Cao, Gianluigi Pillonetto

We consider the identification of large-scale linear and stable dynamic systems whose outputs may be the result of many correlated inputs. Hence, severe ill-conditioning may affect…

eess.SY2021★ 1 cited

Identification of Low Rank Vector Processes

Wenqi Cao, Giorgio Picci, Anders Lindquist

We study modeling and identification of stationary processes with a spectral density matrix of low rank. Equivalently, we consider processes having an innovation of reduced dimensi…

eess.SY2021★ 2 cited

Modeling of Low Rank Time Series

Wenqi Cao, Anders Lindquist, Giorgio Picci

Rank-deficient stationary stochastic vector processes are present in many problems in network theory and dynamic factor analysis. In this paper we study hidden dynamical relations…

eess.SY2020

Modeling and Identification of Low Rank Vector Processes

Giorgio Picci, Wenqi Cao, Anders Lindquist

We study modeling and identification of processes with a spectral density matrix of low rank. Equivalently, we consider processes having an innovation of reduced dimension for whic…

math.DS2020

Spectral Rank, Feedback, Causality and the Indirect Method for CARMA Identification

Wenqi Cao, Anders Lindquist, Giorgio Picci

Building on a recent paper by Georgiou and Lindquist [1] on the problem of rank deficiency of spectral densities and hidden dynamical relations after sampling of continuous-time st…