Pages that link to "Item:Q93618"
From MaRDI portal
The following pages link to Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions (Q93618):
Displaying 50 items.
- Fast and accurate propagation of coherent light (Q2831299) (← links)
- Clustered matrix approximation (Q2834689) (← links)
- A distributed and incremental SVD algorithm for agglomerative data analysis on large networks (Q2834696) (← links)
- Active subspace: toward scalable low-rank learning (Q2840899) (← links)
- Limited memory block Krylov subspace optimization for computing dominant singular value decompositions (Q2847729) (← links)
- A literature survey of low-rank tensor approximation techniques (Q2864808) (← links)
- An Accelerated Divide-and-Conquer Algorithm for the Bidiagonal SVD Problem (Q2936585) (← links)
- On preconditioners for the Laplace double-layer in 2D (Q2948092) (← links)
- A fast, memory efficient and robust sparse preconditioner based on a multifrontal approach with applications to finite‐element matrices (Q2952959) (← links)
- New fast divide-and-conquer algorithms for the symmetric tridiagonal eigenvalue problem (Q2955975) (← links)
- Efficient estimation of eigenvalue counts in an interval (Q2955976) (← links)
- A nonconvex approach to low-rank matrix completion using convex optimization (Q2955982) (← links)
- Multigrid with Rough Coefficients and Multiresolution Operator Decomposition from Hierarchical Information Games (Q2960400) (← links)
- Optimal CUR Matrix Decompositions (Q2968164) (← links)
- Matrices with Hierarchical Low-Rank Structures (Q2971626) (← links)
- IMPROVED ANALYSIS OF THE SUBSAMPLED RANDOMIZED HADAMARD TRANSFORM (Q3101550) (← links)
- (Q3115854) (redirect page) (← links)
- Cost-efficient cutoff method for tensor renormalization group with randomized singular value decomposition (Q3121423) (← links)
- A Randomized Maximum A Posteriori Method for Posterior Sampling of High Dimensional Nonlinear Bayesian Inverse Problems (Q3130408) (← links)
- Randomized Local Model Order Reduction (Q3174769) (← links)
- Hierarchical Interpolative Factorization for Elliptic Operators: Differential Equations (Q3185925) (← links)
- Computing Fundamental Matrix Decompositions Accurately via the Matrix Sign Function in Two Iterations: The Power of Zolotarev's Functions (Q3186101) (← links)
- Compressed Absorbing Boundary Conditions via Matrix Probing (Q3196612) (← links)
- Approximating Spectral Clustering via Sampling: A Review (Q3297374) (← links)
- Optimal experimental design under irreducible uncertainty for linear inverse problems governed by PDEs (Q3298402) (← links)
- Geometric Methods on Low-Rank Matrix and Tensor Manifolds (Q3300541) (← links)
- Randomization and Reweighted $\ell_1$-Minimization for A-Optimal Design of Linear Inverse Problems (Q3300853) (← links)
- Turning Big Data Into Tiny Data: Constant-Size Coresets for $k$-Means, PCA, and Projective Clustering (Q3304733) (← links)
- 6 The Loewner framework for system identification and reduction (Q3384276) (← links)
- Hierarchical Decompositions for the Computation of High-Dimensional Multivariate Normal Probabilities (Q3391110) (← links)
- A Computationally Efficient Projection-Based Approach for Spatial Generalized Linear Mixed Models (Q3391151) (← links)
- Multidimensional Scaling With Very Large Datasets (Q3391174) (← links)
- Compressed and Penalized Linear Regression (Q3391428) (← links)
- Fast Algorithms for Hyperspectral Diffuse Optical Tomography (Q3447464) (← links)
- Scalable Low-Rank Representation (Q3449316) (← links)
- Probabilistic Bounds for the Matrix Condition Number with Extended Lanczos Bidiagonalization (Q3449798) (← links)
- Optimal Low-rank Approximations of Bayesian Linear Inverse Problems (Q3452481) (← links)
- Fast Structured Direct Spectral Methods for Differential Equations with Variable Coefficients, I. The One-Dimensional Case (Q3460272) (← links)
- An approximate linear solver in least square support vector machine using randomized singular value decomposition (Q3461640) (← links)
- Randomized Complete Pivoting for Solving Symmetric Indefinite Linear Systems (Q4556022) (← links)
- Quantum machine learning: a classical perspective (Q4556858) (← links)
- (Q4558196) (← links)
- Modified truncated randomized singular value decomposition (MTRSVD) algorithms for large scale discrete ill-posed problems with general-form regularization (Q4569361) (← links)
- An approximate empirical Bayesian method for large-scale linear-Gaussian inverse problems (Q4571036) (← links)
- A Probabilistic Subspace Bound with Application to Active Subspaces (Q4584918) (← links)
- Computing Low-Rank Approximations of Large-Scale Matrices with the Tensor Network Randomized SVD (Q4584919) (← links)
- Efficient Randomized Algorithms for the Fixed-Precision Low-Rank Matrix Approximation (Q4584924) (← links)
- Randomized algorithms in numerical linear algebra (Q4594242) (← links)
- Practical Sketching Algorithms for Low-Rank Matrix Approximation (Q4598337) (← links)
- Fast Spatial Gaussian Process Maximum Likelihood Estimation via Skeletonization Factorizations (Q4601605) (← links)
