Pages that link to "Item:Q4813564"
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The following pages link to Shannon sampling and function reconstruction from point values (Q4813564):
Displaying 50 items.
- Uniform bounds of aliasing and truncated errors in sampling series of functions from anisotropic Besov class (Q2016652) (← links)
- Random sampling and reconstruction of concentrated signals in a reproducing kernel space (Q2036501) (← links)
- Sampling discretization and related problems (Q2136857) (← links)
- Sampling and reconstruction by means of weighted inverses (Q2187041) (← links)
- Exact asymptotic orders of various randomized widths on Besov classes (Q2191831) (← links)
- Approximation of Lyapunov functions from noisy data (Q2192453) (← links)
- Random sampling in reproducing kernel subspaces of \(L^p(\mathbb{R}^n)\) (Q2195184) (← links)
- Approximation properties of mixed sampling-Kantorovich operators (Q2211155) (← links)
- Worst-case recovery guarantees for least squares approximation using random samples (Q2243884) (← links)
- Sampling and reconstruction of signals in a reproducing kernel subspace of \(L^p(\mathbb R^d)\) (Q2269687) (← links)
- Least-square regularized regression with non-iid sampling (Q2272113) (← links)
- Universality of deep convolutional neural networks (Q2300759) (← links)
- Average sampling and reconstruction of reproducing kernel signals in mixed Lebesgue spaces (Q2325907) (← links)
- Realizations and factorizations of positive definite kernels (Q2330416) (← links)
- Local reconstruction for sampling in shift-invariant spaces (Q2379351) (← links)
- Fully online classification by regularization (Q2381648) (← links)
- Optimal shift invariant spaces and their Parseval frame generators (Q2381655) (← links)
- Learning with sample dependent hypothesis spaces (Q2389476) (← links)
- Application of integral operator for regularized least-square regression (Q2389897) (← links)
- The convergence rates of Shannon sampling learning algorithms (Q2392948) (← links)
- Distributed learning with multi-penalty regularization (Q2415399) (← links)
- Spatially distributed sampling and reconstruction (Q2424626) (← links)
- On approximation by reproducing kernel spaces in weighted \(L^p\) spaces (Q2425847) (← links)
- Learning rates of regularized regression for exponentially strongly mixing sequence (Q2427169) (← links)
- Convergence analysis of online algorithms (Q2454719) (← links)
- Learning gradients by a gradient descent algorithm (Q2480334) (← links)
- Approximation with polynomial kernels and SVM classifiers (Q2498387) (← links)
- Relevant sampling of band-limited functions (Q2509813) (← links)
- A universal envelope for Gaussian processes and their kernels (Q2511412) (← links)
- Approximating and learning by Lipschitz kernel on the sphere (Q2514958) (← links)
- The information-based complexity of approximation problem by adaptive Monte Carlo methods (Q2519328) (← links)
- Shannon sampling. II: Connections to learning theory (Q2581447) (← links)
- Learning dynamical systems using local stability priors (Q2696118) (← links)
- A Sheaf-Theoretic Perspective on Sampling (Q2799928) (← links)
- Proper subspaces and compatibility (Q2804299) (← links)
- Sampling and reconstruction for shift-invariant stochastic processes (Q2875259) (← links)
- Local sampling set conditions in weighted shift-invariant signal spaces (Q2883291) (← links)
- ℓ<sup>1</sup>-Norm support vector machine for ranking with exponentially strongly mixing sequence (Q2930104) (← links)
- Regression learning with non-identically and non-independently sampling (Q2958504) (← links)
- Optimal rate of the regularized regression learning algorithm (Q3008355) (← links)
- Rademacher Chaos Complexities for Learning the Kernel Problem (Q3057230) (← links)
- GENERALIZATION BOUNDS OF REGULARIZATION ALGORITHMS DERIVED SIMULTANEOUSLY THROUGH HYPOTHESIS SPACE COMPLEXITY, ALGORITHMIC STABILITY AND DATA QUALITY (Q3087503) (← links)
- Online regularized generalized gradient classification algorithms (Q3110496) (← links)
- LOCAL LEARNING ESTIMATES BY INTEGRAL OPERATORS (Q3161590) (← links)
- DISCRETIZATION ERROR ANALYSIS FOR TIKHONOV REGULARIZATION (Q3379456) (← links)
- Spectral Algorithms for Supervised Learning (Q3510946) (← links)
- Sampling in Paley-Wiener spaces on combinatorial graphs (Q3533847) (← links)
- Applications of the Bernstein-Durrmeyer operators in estimating the norm of Mercer kernel matrices (Q3538602) (← links)
- Local Sampling and Reconstruction in Shift-Invariant Spaces and Their Applications in Spline Subspaces (Q3578017) (← links)
- ONLINE LEARNING WITH MARKOV SAMPLING (Q3621441) (← links)
