The following pages link to (Q3996207):
Displaying 50 items.
- An approximation problem of noisy data by cubic and bicubic splines (Q693540) (← links)
- Minimax signal detection in ill-posed inverse problems (Q693736) (← links)
- Clustering of functional data in a low-dimensional subspace (Q695680) (← links)
- Local polynomial fitting in semivarying coefficient model (Q697474) (← links)
- Tractability of integration in non-periodic and periodic weighted tensor product Hilbert spaces (Q700172) (← links)
- Irrotational or divergence-free interpolation (Q704807) (← links)
- B-splines and discretization in an inverse problem for Poisson processes (Q707407) (← links)
- Multiscale analysis in Sobolev spaces on bounded domains (Q707583) (← links)
- Spatially adaptive sparse grids for high-dimensional data-driven problems (Q708314) (← links)
- Iteratively regularized Gauss-Newton method for atmospheric remote sensing (Q709339) (← links)
- Numerical differentiation of experimental data: local versus global methods (Q710123) (← links)
- An improved \(C_p\) criterion for spline smoothing (Q710806) (← links)
- Nonparametric denoising of signals of unknown local structure. II: Nonparametric function recovery (Q711050) (← links)
- Efficient algorithms for robust generalized cross-validation spline smoothing (Q711231) (← links)
- Bandwidth-based nonparametric inference (Q713763) (← links)
- Gene-centric gene-gene interaction: a model-based kernel machine method (Q714370) (← links)
- Breaking the curse for uniform approximation in Hilbert spaces via Monte Carlo methods (Q722763) (← links)
- Delaunay-based derivative-free optimization via global surrogates. I: Linear constraints (Q727384) (← links)
- Parametrizations, fixed and random effects (Q730435) (← links)
- Interpolation in reproducing kernel Hilbert spaces based on random subdivision schemes (Q730558) (← links)
- Image inpainting using reproducing kernel Hilbert space and Heaviside functions (Q730583) (← links)
- On regression model selection for the data with correlated errors (Q730754) (← links)
- Discrete approximation by variational vector splines for noisy data (Q730877) (← links)
- Practical use of robust GCV and modified GCV for spline smoothing (Q736591) (← links)
- Structured condition numbers of structured Tikhonov regularization problem and their estimations (Q738977) (← links)
- Minimax convergence rates for kernel CCA (Q739596) (← links)
- Sampled forms of functional PCA in reproducing kernel Hilbert spaces (Q741794) (← links)
- Semiparametric least squares support vector machine for accelerated failure time model (Q744593) (← links)
- Prediction-based regularization using data augmented regression (Q746200) (← links)
- Straightforward intermediate rank tensor product smoothing in mixed models (Q746284) (← links)
- On the relative efficiency of a monotone parameter curve estimator in a functional nonlinear model (Q746292) (← links)
- Another look at linear programming for feature selection via methods of regularization (Q746339) (← links)
- Regularized feature selection in reinforcement learning (Q747290) (← links)
- Data-driven estimation in equilibrium using inverse optimization (Q747777) (← links)
- Fast cross-validation in harmonic approximation (Q778015) (← links)
- Large data and zero noise limits of graph-based semi-supervised learning algorithms (Q778036) (← links)
- Understanding the stochastic partial differential equation approach to smoothing (Q782712) (← links)
- Delaunay-based derivative-free optimization via global surrogates. III: nonconvex constraints (Q785630) (← links)
- Smoothing splines: Regression, derivatives and deconvolution (Q791067) (← links)
- Multivariate Bayesian function estimation (Q818003) (← links)
- The polyharmonic local sine transform: a new tool for local image analysis and synthesis without edge effect (Q818335) (← links)
- Supermix: sparse regularization for mixtures (Q820833) (← links)
- Nonparametric relative recursive regression (Q828048) (← links)
- \(M\)-type penalized splines with auxiliary scale estimation (Q830684) (← links)
- Nonparametric regression, confidence regions and regularization (Q834356) (← links)
- Principal manifold learning by sparse grids (Q836948) (← links)
- The additive hazards model with high-dimensional regressors (Q841068) (← links)
- Accuracy of suboptimal solutions to kernel principal component analysis (Q842769) (← links)
- Automatic model selection for partially linear models (Q842929) (← links)
- Spline methods using integration lattices and digital nets (Q843727) (← links)
