We generalize the concept of adaptive sampling rules to the sketch-and-project method for
solving linear systems. Analyzing adaptive sampling rules in the sketch-and-project setting …

Randomized iterative algorithms have recently been proposed to solve large-scale linear
systems. In this paper, we present a simple randomized extended average block Kaczmarz …

Inspired by the greedy randomized Kaczmarz method, we propose a probability criterion
which can capture subvectors of the residual whose norms are relatively large. According to …

One-bit quantization with time-varying sampling thresholds (also known as random
dithering) has recently found significant utilization potential in statistical signal processing …

Often in applications ranging from medical imaging and sensor networks to error correction
and data science (and beyond), one needs to solve large-scale linear systems in which a …

Stochastic iterative algorithms have gained recent interest in machine learning and signal
processing for solving large-scale systems of equations, Ax=b. One such example is the …

Sketch-and-project is a framework which unifies many known iterative methods for solving
linear systems and their variants, as well as further extensions to nonlinear optimization …

For solving a consistent system of linear equations, the Kaczmarz method is a popular
representative among iterative algorithms due to its simplicity and efficiency. Based on the …

Randomized Kaczmarz-type methods are appealing for large-scale linear systems arising
from big data problems. One of the keys of randomized Kaczmarz-type methods is how to …

The randomized block Kaczmarz method aims to solve linear system A x= b by iteratively
projecting the current estimate to the solution space of a subset of the constraints. Recent …