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 …

The randomized extended Kaczmarz and Gauss–Seidel algorithms have attracted much
attention because of their ability to treat all types of linear systems (consistent or …

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 …

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 …

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 …

In this work we present a new framework for the analysis and design of randomized gossip
algorithms for solving the average consensus problem. We show how classical randomized …

The Kaczmarz method for solving a linear system $ Ax= b $ interprets such a system as a
collection of equations $\left\langle a_i, x\right\rangle= b_i $, where $ a_i $ is the $ i $-th row …

We consider linear systems where consists of normalized rows,, and where up to entries of
have been corrupted (possibly by arbitrarily large numbers). Haddock, Needell, Rebrova & …