Add to ORKGInspired by recent developments in multilevel Monte Carlo (MLMC) methods and randomized sketching for linear algebra problems, we propose an MLMC estimator for real-time processing of matrix structured random data. Our algorithm is particularly effective in handling high-dimensional inner products and matrix multiplication, and finds applications in computer vision and large-scale supervised learning
The purpose of this text is to provide an accessible introduction to a set of recently developed alg...
Abstract. The problem of evaluating the dominant eigenvalue of real matrices using Monte Carlo numer...
This work explores how randomization can be exploited to deliver sophisticated algorithms with prova...
A novel algorithm for computing the action of a matrix exponential over a vector is proposed. The al...
Motivated by applications in which the data may be formulated as a matrix, we consider algorithms fo...
In this paper we deal with performance analysis of Monte Carlo algorithm for large linear algebra pr...
We describe a new Monte Carlo method based on a multilevel method for computing the action of the re...
We study Markov chain Monte Carlo (MCMC) algorithms for target distributions defined on matrix space...
We review the basic outline of the highly successful diffusion Monte Carlo technique com-monly used ...
Available from British Library Document Supply Centre- DSC:DXN057977 / BLDSC - British Library Docum...
A Monte Carlo method for computing the action of a matrix exponential for a certain class of matrice...
This book presents a unified theory of random matrices for applications in machine learning, offerin...
Abstract. In many applications, the data consist of (or may be naturally formulated as) an m × n mat...
... matrix A. It is often of interest to find a low-rank approximation to A, i.e., an approximation ...
We develop a hierarchical matrix construction algorithm using matrix-vector multiplications, based o...
The purpose of this text is to provide an accessible introduction to a set of recently developed alg...
Abstract. The problem of evaluating the dominant eigenvalue of real matrices using Monte Carlo numer...
This work explores how randomization can be exploited to deliver sophisticated algorithms with prova...
A novel algorithm for computing the action of a matrix exponential over a vector is proposed. The al...
Motivated by applications in which the data may be formulated as a matrix, we consider algorithms fo...
In this paper we deal with performance analysis of Monte Carlo algorithm for large linear algebra pr...
We describe a new Monte Carlo method based on a multilevel method for computing the action of the re...
We study Markov chain Monte Carlo (MCMC) algorithms for target distributions defined on matrix space...
We review the basic outline of the highly successful diffusion Monte Carlo technique com-monly used ...
Available from British Library Document Supply Centre- DSC:DXN057977 / BLDSC - British Library Docum...
A Monte Carlo method for computing the action of a matrix exponential for a certain class of matrice...
This book presents a unified theory of random matrices for applications in machine learning, offerin...
Abstract. In many applications, the data consist of (or may be naturally formulated as) an m × n mat...
... matrix A. It is often of interest to find a low-rank approximation to A, i.e., an approximation ...
We develop a hierarchical matrix construction algorithm using matrix-vector multiplications, based o...
The purpose of this text is to provide an accessible introduction to a set of recently developed alg...
Abstract. The problem of evaluating the dominant eigenvalue of real matrices using Monte Carlo numer...
This work explores how randomization can be exploited to deliver sophisticated algorithms with prova...