2 citations · 4 across the 6 of their papers we have counts for
6 papers
On Conditional Independence Graph Learning From Multi-Attribute Gaussian Dependent Time Series
Jitendra K. Tugnait
Estimation of the conditional independence graph (CIG) of high-dimensional multivariate Gaussian time series from multi-attribute data is considered. Existing methods for graph est…
Learning Conditional Independence Differential Graphs From Time-Dependent Data
Jitendra K Tugnait
Estimation of differences in conditional independence graphs (CIGs) of two time series Gaussian graphical models (TSGGMs) is investigated where the two TSGGMs are known to have sim…
Multi-Attribute Graph Estimation with Sparse-Group Non-Convex Penalties
Jitendra K Tugnait
We consider the problem of inferring the conditional independence graph (CIG) of high-dimensional Gaussian vectors from multi-attribute data. Most existing methods for graph estima…
Learning Multi-Attribute Differential Graphs with Non-Convex Penalties
Jitendra K Tugnait
We consider the problem of estimating differences in two multi-attribute Gaussian graphical models (GGMs) which are known to have similar structure, using a penalized D-trace loss…
Graph Learning from Multivariate Dependent Time Series via a Multi-Attribute Formulation
Jitendra K Tugnait
We consider the problem of inferring the conditional independence graph (CIG) of a high-dimensional stationary multivariate Gaussian time series. In a time series graph, each compo…
Sparse-Group Log-Sum Penalized Graphical Model Learning For Time Series
Jitendra K Tugnait
We consider the problem of inferring the conditional independence graph (CIG) of a high-dimensional stationary multivariate Gaussian time series. A sparse-group lasso based frequen…