Imagen de Portada

Smoothed Analysis of the Condition Numbers and Growth Factors of Matrices

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Sankar, Arvind, Spielman, Daniel A., Teng, Shang-Hua
Formato:	Preprint
Publicado:	2003
Materias:	Numerical Analysis Data Structures and Algorithms G.1.3
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Solving Sparse, Symmetric, Diagonally-Dominant Linear Systems in Time $O (m^{1.31})$
por: Spielman, Daniel A., et al.
Publicado: (2003)

Nearly-Linear Time Algorithms for Preconditioning and Solving Symmetric, Diagonally Dominant Linear Systems
por: Spielman, Daniel A., et al.
Publicado: (2006)

Smoothed Analysis of Interior-Point Algorithms: Condition Number
por: Dunagan, John, et al.
Publicado: (2003)

Fast Approximate Determinants Using Rational Functions
por: Colthurst, Thomas, et al.
Publicado: (2024)

Debiasing Polynomial and Fourier Regression
por: Camaño, Chris, et al.
Publicado: (2025)

Some problems in asymptotic convex geometry and random matrices motivated by numerical algorithms
por: Vershynin, Roman
Publicado: (2007)

Faster Linear Algebra Algorithms with Structured Random Matrices
por: Camaño, Chris, et al.
Publicado: (2025)

Entrywise Approximate Solutions for SDDM Systems in Almost-Linear Time
por: Farfan, Angelo, et al.
Publicado: (2025)

Undercomplete Decomposition of Symmetric Tensors in Linear Time, and Smoothed Analysis of the Condition Number
por: Koiran, Pascal, et al.
Publicado: (2024)

Universal Matrix Sparsifiers and Fast Deterministic Algorithms for Linear Algebra
por: Bhattacharjee, Rajarshi, et al.
Publicado: (2023)

Improved Spectral Density Estimation via Explicit and Implicit Deflation
por: Bhattacharjee, Rajarshi, et al.
Publicado: (2024)

Hutchinson's Estimator is Bad at Kronecker-Trace-Estimation
por: Meyer, Raphael A., et al.
Publicado: (2023)

Understanding the Kronecker Matrix-Vector Complexity of Linear Algebra
por: Meyer, Raphael A., et al.
Publicado: (2025)

A Hardware Accelerator for the Goemans-Williamson Algorithm
por: Herrera-Martí, D. A., et al.
Publicado: (2025)

Does block size matter in randomized block Krylov low-rank approximation?
por: Chen, Tyler, et al.
Publicado: (2025)

Linear-Time Approximation Algorithms for Computing Numerical Summation with Provably Small Errors
por: Kao, Ming-Yang, et al.
Publicado: (1999)

Sublinear Time Low-Rank Approximation of Hankel Matrices
por: Kapralov, Michael, et al.
Publicado: (2025)

Sublinear Time Low-Rank Approximation of Toeplitz Matrices
por: Musco, Cameron, et al.
Publicado: (2024)

Model-Based Learning of Whittle indices
por: Charles-Rebuffé, Joël, et al.
Publicado: (2025)

Block Encoding of Sparse Matrices via Coherent Permutation
por: Setty, Abhishek
Publicado: (2025)

Analysis of Different Algorithmic Design Techniques for Seam Carving
por: Aijaz, Owais, et al.
Publicado: (2024)

Stochastic Rounding 2.0, with a View towards Complexity Analysis
por: Drineas, Petros, et al.
Publicado: (2024)

Mixed-Precision in High-Order Methods: the Impact of Floating-Point Precision on the ADER-DG Algorithm
por: Marot-Lassauzaie, Marc, et al.
Publicado: (2025)

Two Iterative Algorithms for Solving Systems of Simultaneous Linear Algebraic Equations with Real Matrices of Coefficients
por: Kondratiev, A. S., et al.
Publicado: (2005)

Complete Decomposition of Symmetric Tensors in Linear Time and Polylogarithmic Precision
por: Koiran, Pascal, et al.
Publicado: (2022)

Fast One-Pass Sparse Approximation of the Top Eigenvectors of Huge Approximately Low-Rank Matrices? Yes, $MAM^*$!
por: Boahen, Edem, et al.
Publicado: (2025)

Linear Systems and Eigenvalue Problems: Open Questions from a Simons Workshop
por: Amsel, Noah, et al.
Publicado: (2026)

Complex Mean and Variance of Linear Regression Model for High-Noised Systems by Kriging
por: Suslo, Tomasz
Publicado: (2005)

The Lanczos algorithm for matrix functions: a handbook for scientists
por: Chen, Tyler
Publicado: (2024)

Algorithms and data structures for numerical computations with automatic precision estimation
por: Netay, Igor V.
Publicado: (2024)

Near-optimal hierarchical matrix approximation from matrix-vector products
por: Chen, Tyler, et al.
Publicado: (2024)

Stability of the Lanczos Method for Matrix Function Approximation
por: Musco, Cameron, et al.
Publicado: (2017)

Randomized matrix-free quadrature: unified and uniform bounds for stochastic Lanczos quadrature and the kernel polynomial method
por: Chen, Tyler, et al.
Publicado: (2022)

Structural Optimal Jacobian Accumulation and Minimum Edge Count are NP-Complete Under Vertex Elimination
por: Bentert, Matthias, et al.
Publicado: (2025)

Fixed-sparsity matrix approximation from matrix-vector products
por: Amsel, Noah, et al.
Publicado: (2024)

Block subsampled randomized Hadamard transform for low-rank approximation on distributed architectures
por: Balabanov, Oleg, et al.
Publicado: (2022)

Revisiting Approximate Leverage Score Sketching for Matrix Least Squares
por: Larsen, Brett W., et al.
Publicado: (2022)

Fast algorithms for least square problems with Kronecker lower subsets
por: Malik, Osman Asif, et al.
Publicado: (2022)

Preserving Extreme Singular Values with One Oblivious Sketch
por: Mango, John M., et al.
Publicado: (2025)

Finer-Grained Hardness of Kernel Density Estimation
por: Alman, Josh, et al.
Publicado: (2024)