4 papers
Structure Learning in Graphical Models from Indirect Observations
Hang Zhang, Afshin Abdi, Faramarz Fekri
This paper considers learning of the graphical structure of a -dimensional random vector using both parametric and non-parametric methods. Unlike the previous works…
A General Compressive Sensing Construct using Density Evolution
Hang Zhang, Afshin Abdi, Faramarz Fekri
This paper proposes a general framework to design a sparse sensing matrix $\ensuremath{\mathbf{A}}\in \mathbb{R}^{m\times n}$, in a linear measurement system $\ensuremath{\mathbf{y…
The Benefits of Diversity: Permutation Recovery in Unlabeled Sensing from Multiple Measurement Vectors
Hang Zhang, Martin Slawski, Ping Li
In "Unlabeled Sensing", one observes a set of linear measurements of an underlying signal with incomplete or missing information about their ordering, which can be modeled in terms…
Compressive Sensing with a Multiple Convex Sets Domain
Hang Zhang, Afshin Abdi, Faramarz Fekri
In this paper, we study a general framework for compressive sensing assuming the existence of the prior knowledge that belongs to the union of multiple convex se…