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.
- A signal theory approach to support vector classification: the sinc kernel (Q280313) (← links)
- Improved sampling and reconstruction in spline subspaces (Q287890) (← links)
- Multi-penalty regularization in learning theory (Q306697) (← links)
- Regularized restoration for two dimensional band-limited signals (Q335950) (← links)
- Learning rates of regularized regression on the unit sphere (Q365838) (← links)
- Regularized least square regression with unbounded and dependent sampling (Q369717) (← links)
- The learning rate of \(l_2\)-coefficient regularized classification with strong loss (Q383667) (← links)
- Generalization bounds of ERM algorithm with Markov chain samples (Q403479) (← links)
- Learning from regularized regression algorithms with \(p\)-order Markov chain sampling (Q423185) (← links)
- Generalization bounds of ERM algorithm with \(V\)-geometrically ergodic Markov chains (Q429786) (← links)
- Learning rates for multi-kernel linear programming classifiers (Q537615) (← links)
- Learning from non-identical sampling for classification (Q541601) (← links)
- Frames, Riesz bases, and sampling expansions in Banach spaces via semi-inner products (Q544035) (← links)
- The ill-posedness of restoring lost samples and regularized restoration for band-limited signals (Q548910) (← links)
- Concentration estimates for learning with \(\ell ^{1}\)-regularizer and data dependent hypothesis spaces (Q550498) (← links)
- Error estimates from noise samples for iterative algorithm in shift-invariant signal spaces (Q610861) (← links)
- Random sampling of bandlimited functions (Q611016) (← links)
- Least square regression with indefinite kernels and coefficient regularization (Q617706) (← links)
- On complex-valued 2D eikonals. IV: continuation past a caustic (Q627030) (← links)
- Convergence rate of kernel canonical correlation analysis (Q659987) (← links)
- A regularized two-dimensional sampling algorithm (Q682033) (← links)
- Random sampling in shift invariant spaces (Q691805) (← links)
- Variational splines and Paley-Wiener spaces on Combinatorial graphs (Q734052) (← links)
- Sampling, Marcinkiewicz-Zygmund inequalities, approximation, and quadrature rules (Q783725) (← links)
- Weyl eigenvalue asymptotics and sharp adaptation on vector bundles (Q842915) (← links)
- Geometry on probability spaces (Q843724) (← links)
- Hermite learning with gradient data (Q848563) (← links)
- Regularized least square regression with dependent samples (Q849335) (← links)
- Sampling theory, oblique projections and a question by Smale and Zhou (Q849684) (← links)
- Nonlinear function approximation: computing smooth solutions with an adaptive greedy algorithm (Q863343) (← links)
- Multi-kernel regularized classifiers (Q870343) (← links)
- Learning theory approach to a system identification problem involving atomic norm (Q895425) (← links)
- Multi-variate Hardy-type lattice point summation and Shannon-type sampling (Q901330) (← links)
- The role of frame force in quantum detection (Q929331) (← links)
- Reproducing kernel Hilbert spaces associated with analytic translation-invariant Mercer kernels (Q939089) (← links)
- Derivative reproducing properties for kernel methods in learning theory (Q939547) (← links)
- Orthogonality from disjoint support in reproducing kernel Hilbert spaces (Q952158) (← links)
- Parzen windows for multi-class classification (Q958247) (← links)
- Moving least-square method in learning theory (Q968963) (← links)
- Estimates of the approximation error using Rademacher complexity: Learning vector-valued functions (Q1008456) (← links)
- Learning from uniformly ergodic Markov chains (Q1023402) (← links)
- General A-P iterative algorithm in shift-invariant spaces (Q1034278) (← links)
- Reconstructing signals with finite rate of innovation from noisy samples (Q1038748) (← links)
- Estimates of the norm of the Mercer kernel matrices with discrete orthogonal transforms (Q1046859) (← links)
- High order Parzen windows and randomized sampling (Q1047130) (← links)
- Learning a function from noisy samples at a finite sparse set of points (Q1048968) (← links)
- Gradient learning in a classification setting by gradient descent (Q1048984) (← links)
- Metric duality between positive definite kernels and boundary processes (Q1700429) (← links)
- Analysis of approximation by linear operators on variable \(L_\rho^{p(\cdot)}\) spaces and applications in learning theory (Q1724144) (← links)
- The generalization performance of ERM algorithm with strongly mixing observations (Q1959486) (← links)
