Substantial progress has been made recently on develo** provably accurate and efficient
algorithms for low-rank matrix factorization via nonconvex optimization. While conventional …

The problem of phase retrieval, ie, the recovery of a function given the magnitude of its
Fourier transform, arises in various fields of science and engineering, including electron …

This article deals with the problem of adaptive target detection in the presence of
homogeneous Gaussian interference with frequency diverse array multiple-input multiple …

We study the problem of recovering the phase from magnitude measurements; specifically,
we wish to reconstruct a complex-valued signal about which we have phaseless samples of …

Can we recover a complex signal from its Fourier magnitudes? More generally, given a set
of m measurements, y_k=\left| a _k^* x\right| yk= ak∗ x for k= 1, ..., mk= 1,…, m, is it possible …

Low-rank matrices play a fundamental role in modeling and computational methods for
signal processing and machine learning. In many applications where low-rank matrices …

This paper presents a new algorithm, termed truncated amplitude flow (TAF), to recover an
unknown vector x from a system of quadratic equations of the form yi=|< ai, x>| 2, where ai's …

Manifold optimization is ubiquitous in computational and applied mathematics, statistics,
engineering, machine learning, physics, chemistry, etc. One of the main challenges usually …

A wavelet scattering network computes a translation invariant image representation which is
stable to deformations and preserves high-frequency information for classification. It …

A scattering transform defines a locally translation invariant representation which is stable to
time-war** deformation. It extends MFCC representations by computing modulation …