scientific article; zbMATH DE number 7049758
From MaRDI portal
Publication:4633051
zbMath1484.62037arXiv1708.01945MaRDI QIDQ4633051
Miles E. Lopes, Michael W. Mahoney, Shu-Sen Wang
Publication date: 2 May 2019
Full work available at URL: https://arxiv.org/abs/1708.01945
Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Parametric inference (62F99) Nonparametric statistical resampling methods (62G09) Random matrices (algebraic aspects) (15B52)
Related Items (4)
Measuring the Algorithmic Convergence of Randomized Ensembles: The Regression Setting ⋮ Efficient Error and Variance Estimation for Randomized Matrix Computations ⋮ Estimating the algorithmic variance of randomized ensembles via the bootstrap ⋮ Bootstrapping the operator norm in high dimensions: error estimation for covariance matrices and sketching
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions
- Empirical and multiplier bootstraps for suprema of empirical processes of increasing complexity, and related Gaussian couplings
- Gaussian approximation of suprema of empirical processes
- Faster least squares approximation
- Estimating the algorithmic variance of randomized ensembles via the bootstrap
- Hanson-Wright inequality and sub-Gaussian concentration
- Fast matrix multiplication is stable
- A fast randomized algorithm for the approximation of matrices
- Fast dimension reduction using Rademacher series on dual BCH codes
- Best constants in moment inequalities for linear combinations of independent and exchangeable random variables
- Extrapolation methods theory and practice
- Sub-sampled Newton methods
- Gaussian and bootstrap approximations for high-dimensional U-statistics and their applications
- Weak convergence and empirical processes. With applications to statistics
- Comparison and anti-concentration bounds for maxima of Gaussian random vectors
- Central limit theorems and bootstrap in high dimensions
- Gaussian approximations and multiplier bootstrap for maxima of sums of high-dimensional random vectors
- Improved Matrix Algorithms via the Subsampled Randomized Hadamard Transform
- Approximate nearest neighbors and the fast Johnson-Lindenstrauss transform
- Computational Advertising: Techniques for Targeting Relevant Ads
- Newton Sketch: A Near Linear-Time Optimization Algorithm with Linear-Quadratic Convergence
- Sketching Sparse Matrices, Covariances, and Graphs via Tensor Products
- Randomized algorithms for the low-rank approximation of matrices
- Randomized Algorithms for Matrices and Data
- Blendenpik: Supercharging LAPACK's Least-Squares Solver
- Low-Rank Approximation and Regression in Input Sparsity Time
- Estimating Extremal Eigenvalues and Condition Numbers of Matrices
- Extensions of Lipschitz mappings into a Hilbert space
- Sampling algorithms for l2 regression and applications
- Relative-Error $CUR$ Matrix Decompositions
- Practical Extrapolation Methods
- Accuracy and Stability of Numerical Algorithms
- Checking approximate computations over the reals
- Comparing large covariance matrices under weak conditions on the dependence structure and its application to gene clustering
- Low Rank Matrix-Valued Chernoff Bounds and Approximate Matrix Multiplication
- Fast Monte Carlo Algorithms for Matrices I: Approximating Matrix Multiplication
- Compressed matrix multiplication
- Robust Statistics
This page was built for publication: