Pages that link to "Item:Q2540916"

The following pages link to Some results on Tchebycheffian spline functions and stochastic processes (Q2540916):

Displaying 50 items.

• Understanding neural networks with reproducing kernel Banach spaces (Q2105111) (← links)
• Approximate kernel PCA: computational versus statistical trade-off (Q2105193) (← links)
• Solving and learning nonlinear PDEs with Gaussian processes (Q2133484) (← links)
• Stochastic functional linear models and Malliavin calculus (Q2135880) (← links)
• Fast quantile regression in reproducing kernel Hilbert space (Q2151599) (← links)
• Restoration of the product consumption rate with integral cubic smoothing spline, study of the best smoothing parameter choice (Q2154904) (← links)
• Functional single-index quantile regression models (Q2195823) (← links)
• From Gauss to Kolmogorov: localized measures of complexity for ellipses (Q2199701) (← links)
• A conversation with Grace Wahba (Q2218048) (← links)
• A unifying representer theorem for inverse problems and machine learning (Q2231644) (← links)
• Spectrally-truncated kernel ridge regression and its free lunch (Q2233553) (← links)
• Efficient regularized least-squares algorithms for conditional ranking on relational data (Q2251443) (← links)
• Sparse and efficient estimation for partial spline models with increasing dimension (Q2255168) (← links)
• A class of semi-supervised support vector machines by DC programming (Q2256780) (← links)
• A generalized Newton algorithm for quantile regression models (Q2259794) (← links)
• Composite support vector quantile regression estimation (Q2259813) (← links)
• Approximation of kernel matrices by circulant matrices and its application in kernel selection methods (Q2266837) (← links)
• A fast quasi-Newton method for semi-supervised SVM (Q2275982) (← links)
• Conditional probability estimation based classification with class label missing at random (Q2293539) (← links)
• A penalized likelihood method for nonseparable space-time generalized additive models (Q2316739) (← links)
• Distribution-free uncertainty quantification for kernel methods by gradient perturbations (Q2320596) (← links)
• On nonparametric randomized sketches for kernels with further smoothness (Q2322682) (← links)
• Nonlinear system identification via data augmentation (Q2327384) (← links)
• Solution path for quantile regression with epsilon-insensitive loss in a reproducing kernel Hilbert space (Q2405941) (← links)
• Functional reproducing kernel Hilbert spaces for non-point-evaluation functional data (Q2415404) (← links)
• Substationarity for spatial point processes (Q2418502) (← links)
• When is there a representer theorem? Nondifferentiable regularisers and Banach spaces (Q2423813) (← links)
• Penalized empirical likelihood estimation of semiparametric models (Q2426738) (← links)
• Non-crossing quantile regression via doubly penalized kernel machine (Q2430224) (← links)
• About the non-convex optimization problem induced by non-positive semidefinite kernel learning (Q2442765) (← links)
• A sparse large margin semi-supervised learning method (Q2511744) (← links)
• Analytical and numerical approximation formulas for the Fourier multiplier operators (Q2514174) (← links)
• Convergence rates of certain approximate solutions to Fredholm integral equations of the first kind (Q2557556) (← links)
• A class of approximate solutions to linear operator equations (Q2562995) (← links)
• Getting better contour plots with S and GCVPACK (Q2563656) (← links)
• Constructing Bayesian formulations of sparse kernel learning methods (Q2568020) (← links)
• Efficient wavelet adaptation for hybrid wavelet -- large margin classifiers (Q2568080) (← links)
• Quantiles, expectiles and splines (Q2630078) (← links)
• Generalized semi-inner products with applications to regularized learning (Q2637940) (← links)
• On reproducing kernel Banach spaces: generic definitions and unified framework of constructions (Q2674395) (← links)
• Large dynamic covariance matrix estimation with an application to portfolio allocation: a semiparametric reproducing kernel Hilbert space approach (Q2674937) (← links)
• Nonparametric smoothing using state space techniques (Q2738918) (← links)
• Sparse on-line Gaussian processes (Q2780851) (← links)
• Supervised Learning by Support Vector Machines (Q2789826) (← links)
• Nonlinear adaptive filtering using kernel-based algorithms with dictionary adaptation (Q2793962) (← links)
• Universalities of reproducing kernels revisited (Q2825334) (← links)
• Extremal functions on Sobolev–Dunkl spaces (Q2854305) (← links)
• A review of stochastic algorithms with continuous value function approximation and some new approximate policy iteration algorithms for multidimensional continuous applications (Q2887630) (← links)
• Powerful tests for detecting a gene effect in the presence of possible gene-gene interactions using garrote kernel machines (Q2893383) (← links)
• Performance of robust GCV and modified GCV for spline smoothing (Q2911706) (← links)