Multiscale data sampling and function extension
From MaRDI portal
Publication:1762316
DOI10.1016/j.acha.2012.03.002zbMath1262.65016OpenAlexW2002639489MaRDI QIDQ1762316
Amit Bermanis, Amir Z. Averbuch, Ronald R. Coifman
Publication date: 23 November 2012
Published in: Applied and Computational Harmonic Analysis (Search for Journal in Brave)
Full work available at URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.409.4617
Gaussian kerneldiffusion mapsmultiscale decompositionnumerical rankgeometric harmonicsmultiscale schemeNyström interpolation methodsampling scattered data
Related Items (19)
Diffusion-based kernel methods on Euclidean metric measure spaces ⋮ Learning from patches by efficient spectral decomposition of a structured kernel ⋮ \textsf{StreaMRAK} a streaming multi-resolution adaptive kernel algorithm ⋮ Grassmannian diffusion maps based surrogate modeling via geometric harmonics ⋮ Reprint of: A forward-backward greedy approach for sparse multiscale learning ⋮ Randomized LU decomposition ⋮ Hierarchical regularization networks for sparsification based learning on noisy datasets ⋮ Patch-to-tensor embedding ⋮ Updating kernel methods in spectral decomposition by affinity perturbations ⋮ A low discrepancy sequence on graphs ⋮ Cover-based bounds on the numerical rank of Gaussian kernels ⋮ Inverting nonlinear dimensionality reduction with scale-free radial basis function interpolation ⋮ Diffusion representations ⋮ Geometric component analysis and its applications to data analysis ⋮ Numerical integration on graphs: Where to sample and how to weigh ⋮ Two directional Laplacian pyramids with application to data imputation ⋮ A forward-backward greedy approach for sparse multiscale learning ⋮ Fast and Accurate Gaussian Kernel Ridge Regression Using Matrix Decompositions for Preconditioning ⋮ Parameter Rating by Diffusion Gradient
This page was built for publication: Multiscale data sampling and function extension