Binary measurements arise naturally in a variety of statistics and engineering applications.
They may be inherent to the problem-for example, in determining the relationship between …

Compressed sensing (CS) has been applied to magnetic resonance imaging for the
acceleration of data collection. However, existing CS techniques usually produce images …

We introduce two new algorithms, Serial-ℓ 0 and Parallel-ℓ 0 for solving a large
underdetermined linear system of equations y= A x∈ R m when it is known that x∈ R n has …

We develop a two-part reconstruction framework for signal recovery in compressed sensing
(CS), where a fast algorithm is applied to provide partial recovery in Part 1, and a CS …

Compressed sensing (CS) using sparse measurement matrices and iterative
messagepassing reconstruction algorithms have been recently investigated as a low …

This thesis presents a series of algorithmic innovations in Combinatorial Compressed
Sensing and Persistent Homology. The unifying strategy across these contributions is in …

Page 1 ABSTRACT MA, YANTING. Solving Large-Scale Inverse Problems via Approximate
Message Passing and Optimization. (Under the direction of Dror Baron.) This work studies the …

Minimizing scan time without compromising image quality has been the main thrust of
magnetic resonance imaging (MRI) since the establishment of the field. Tremendous effort …

Compressed sensing (CS) using sparse measurement matrices and iterative
messagepassing reconstruction algorithms have been recently investigated as a low …

Compressed Sensing (CS) methods using sparse binary measurement matrices and
iterative message-passing recovery procedures have been recently investigated due to their …