Pages that link to "Item:Q93618"

The following pages link to Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions (Q93618):

Displaying 50 items.

• Randomized block Krylov methods for approximating extreme eigenvalues (Q2068363) (← links)
• Tikhonov regularization with MTRSVD method for solving large-scale discrete ill-posed problems (Q2068645) (← links)
• Faster tensor train decomposition for sparse data (Q2068649) (← links)
• An adaptation for iterative structured matrix completion (Q2072669) (← links)
• Intrusive and data-driven reduced order modelling of the rotating thermal shallow water equation (Q2079107) (← links)
• Space-fractional diffusion with variable order and diffusivity: discretization and direct solution strategies (Q2084920) (← links)
• A novel update rule of HALS algorithm for nonnegative matrix factorization and Zangwill's global convergence (Q2089877) (← links)
• Triad second renormalization group (Q2092639) (← links)
• Efficient randomized tensor-based algorithms for function approximation and low-rank kernel interactions (Q2093707) (← links)
• An enhanced algorithm for online proper orthogonal decomposition and its parallelization for unsteady simulations (Q2094341) (← links)
• Local Lagrangian reduced-order modeling for the Rayleigh-Taylor instability by solution manifold decomposition (Q2099719) (← links)
• Sensitivity of low-rank matrix recovery (Q2100520) (← links)
• Deep-HyROMnet: a deep learning-based operator approximation for hyper-reduction of nonlinear parametrized PDEs (Q2103427) (← links)
• Nonlinear matrix recovery using optimization on the Grassmann manifold (Q2105129) (← links)
• Approximate kernel PCA: computational versus statistical trade-off (Q2105193) (← links)
• Forward and inverse modeling of fault transmissibility in subsurface flows (Q2107210) (← links)
• Single-pass randomized QLP decomposition for low-rank approximation (Q2107279) (← links)
• Bootstrapping the operator norm in high dimensions: error estimation for covariance matrices and sketching (Q2108486) (← links)
• A probabilistic algorithm for aggregating vastly undersampled large Markov chains (Q2115692) (← links)
• Pass-efficient methods for compression of high-dimensional turbulent flow data (Q2123807) (← links)
• Wavelet adaptive proper orthogonal decomposition for large-scale flow data (Q2124744) (← links)
• Optimal design of acoustic metamaterial cloaks under uncertainty (Q2128381) (← links)
• Randomized approaches to accelerate MCMC algorithms for Bayesian inverse problems (Q2129320) (← links)
• On condition numbers of the total least squares problem with linear equality constraint (Q2129641) (← links)
• Spectral estimation from simulations via sketching (Q2133499) (← links)
• Approximate inversion of discrete Fourier integral operators (Q2133539) (← links)
• Physics-informed machine learning for reduced-order modeling of nonlinear problems (Q2133556) (← links)
• Sparse data-driven quadrature rules via \(\ell^p\)-quasi-norm minimization (Q2134455) (← links)
• Reduced multidimensional scaling (Q2135844) (← links)
• A fast regression via SVD and marginalization (Q2135884) (← links)
• Multilinear POD-DEIM model reduction for 2D and 3D semilinear systems of differential equations (Q2136223) (← links)
• Functional principal subspace sampling for large scale functional data analysis (Q2137809) (← links)
• Variational inference at glacier scale (Q2137912) (← links)
• On the best approximation algorithm by low-rank matrices in Chebyshev's norm (Q2149032) (← links)
• Error analysis of a model order reduction framework for financial risk analysis (Q2153946) (← links)
• Model order reduction method based on (r)POD-ANNs for parameterized time-dependent partial differential equations (Q2158140) (← links)
• Randomized quaternion QLP decomposition for low-rank approximation (Q2162234) (← links)
• An efficient algorithm for computing the approximate t-URV and its applications (Q2162323) (← links)
• Sparse latent factor regression models for genome-wide and epigenome-wide association studies (Q2162483) (← links)
• Randomized approximate class-specific kernel spectral regression analysis for large-scale face verification (Q2163243) (← links)
• Multiscale regression on unknown manifolds (Q2167604) (← links)
• A dynamic mode decomposition technique for the analysis of non-uniformly sampled flow data (Q2168306) (← links)
• Randomized QLP decomposition (Q2176120) (← links)
• On variable and random shape Gaussian interpolations (Q2177866) (← links)
• A sketched finite element method for elliptic models (Q2180458) (← links)
• Multiscale-spectral GFEM and optimal oversampling (Q2180477) (← links)
• The stability of the first Neumann Laplacian eigenfunction under domain deformations and applications (Q2197953) (← links)
• An optimization problem based on a Bayesian approach for the 2D Helmholtz equation (Q2210330) (← links)
• Revisiting the low-rank eigenvalue problem (Q2213691) (← links)
• Reduction of multivariate mixtures and its applications (Q2214625) (← links)