Mercer’s Theorem, Feature Maps, and Smoothing
From MaRDI portal
Publication:5307566
DOI10.1007/11776420_14zbMath1143.68554OpenAlexW1489867037MaRDI QIDQ5307566
Yuan Yao, Ha Quang Minh, Partha Niyogi
Publication date: 14 September 2007
Published in: Learning Theory (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/11776420_14
Nonparametric regression and quantile regression (62G08) Learning and adaptive systems in artificial intelligence (68T05)
Related Items
A general non-local denoising model using multi-kernel-induced measures ⋮ Solving Fredholm integral equation of the first kind using Gaussian process regression ⋮ Interactions Between Kernels, Frames, and Persistent Homology ⋮ A nonlinear data-driven reduced order model for computational homogenization with physics/pattern-guided sampling ⋮ Some remarks on MCMC estimation of spectra of integral operators ⋮ Spectral approach for kernel-based interpolation ⋮ Robust kernel ridge regression based on M-estimation ⋮ Benchmarking different clustering algorithms on functional data ⋮ Polyharmonic approximation on the sphere ⋮ A note on kernel principal component regression ⋮ Unnamed Item ⋮ Nonparametric distributed learning under general designs ⋮ A close look at the entropy numbers of the unit ball of the reproducing Hilbert space of isotropic positive definite kernels ⋮ Asymptotics and practical aspects of testing normality with kernel methods ⋮ Kernel embedding based variational approach for low-dimensional approximation of dynamical systems ⋮ Sharp estimates for eigenvalues of integral operators generated by dot product kernels on the sphere ⋮ Integral operators on the sphere generated by positive definite smooth kernels ⋮ Diffusion maps for changing data ⋮ Mercer Kernels and Integrated Variance Experimental Design: Connections Between Gaussian Process Regression and Polynomial Approximation ⋮ Super-exponential decay rates for eigenvalues and singular values of integral operators on the sphere ⋮ Image and video colorization using vector-valued reproducing kernel Hilbert spaces ⋮ A novel embedded min-max approach for feature selection in nonlinear support vector machine classification ⋮ Infinite-dimensional log-determinant divergences between positive definite trace class operators ⋮ A spectral series approach to high-dimensional nonparametric regression ⋮ Descriptions, Discretizations, and Comparisons of Time/Space Colored and White Noise Forcings of the Navier--Stokes Equations ⋮ Robust non-parametric regression via incoherent subspace projections ⋮ The role of Hilbert-Schmidt SVD basis in Hermite-Birkhoff interpolation in fractional sense ⋮ A regression perspective on generalized distance covariance and the Hilbert-Schmidt independence criterion ⋮ High-Dimensional Data Classification