Random projections for the nonnegative least-squares problem

DOI10.1016/j.laa.2009.03.026zbMath1167.65032OpenAlexW2120565458MaRDI QIDQ1030739

Christos Boutsidis, Petros Drineas

Publication date: 2 July 2009

Published in: Linear Algebra and its Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.laa.2009.03.026

zbMATH Keywords

samplingconvex optimizationnumerical examplesquadratic optimizationrandomized algorithmHadamard transformrandom projectionsfast Johnson-Lindestrauss transformleast-squares regression problemsnon negative least-squaresoptimum nonnegative solution

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Convex programming (90C25) Quadratic programming (90C20)

Related Items (8)

Randomized generalized singular value decomposition ⋮ Sign-constrained least squares estimation for high-dimensional regression ⋮ The Weighted Nonnegative Least-Squares Problem with Implicitly Characterized Points ⋮ On b-bit min-wise hashing for large-scale regression and classification with sparse data ⋮ Unnamed Item ⋮ Multiplicative perturbation bounds for multivariate multiple linear regression in Schatten \(p\)-norms ⋮ Stochastic boundary methods of fundamental solutions for solving PDEs ⋮ Approximate nonparametric quantile regression in reproducing kernel Hilbert spaces via random projection

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Faster least squares approximation
• Approximate nearest neighbors and the fast Johnson-Lindenstrauss transform
• Sampling from large matrices
• Sampling algorithms for l₂ regression and applications
• An interior point Newton-like method for non-negative least-squares problems with degenerate solution
• Nonnegative Matrix Factorization Based on Alternating Nonnegativity Constrained Least Squares and Active Set Method
• Relative-Error $CUR$ Matrix Decompositions
• On computational aspects of bounded linear least squares problems
• Extensions and Applications of the Householder Algorithm for Solving Linear Least Squares Problems

This page was built for publication: Random projections for the nonnegative least-squares problem