We propose a new algorithm for the problem of recovering data that adheres to multiple,
heterogenous low-dimensional structures from linear observations. Focussing on data …

The problem of recovering a signal $\boldsymbol {x}\in\mathbb {R}^ n $ from a quadratic
system $\{y_i=\boldsymbol {x}^\top\boldsymbol {A} _i\boldsymbol {x},\i= 1,\ldots, m\} $ with …

In this paper, we present modifications of the iterative hard thresholding (IHT) method for
recovery of jointly row-sparse and low-rank matrices. In particular, a Riemannian version of …

Aiming at the problem that multi-highlight bearing resolution of underwater target, a high-
resolution reconstruction of multi-highlight bearings resolution of underwater target with L1 …

In many applications, one is faced with an inverse problem, where the known signal
depends in a bilinear way on two unknown input vectors. Often at least one of the input …

Multi-view clustering (MVC) algorithms usually have good performance which benefits from
the merit that multi-view data contains more comprehensive information. Generally, most …

In this paper, we first propose a simple and unified approach to stability of phaseless
operator to both amplitude and intensity measurement, both complex and real cases on …

We consider the problem of recovering an unknown low-rank matrix X⋆ with (possibly) non-
orthogonal, effectively sparse rank-1 decomposition from measurements y gathered in a …

It may be one of mankind's most profound desires to “understand whatever; Binds the
world's innermost core together”,[, ll. 382–383] to put it in the words of Goethe. This ambition …

This dissertation studies the performance of convex and non-convex algorithms for
randomized bilinear inverse problems. In particular, we examine algorithmic approaches …