The following pages link to (Q3148817):
Displaying 50 items.
- Functional estimation of anisotropic covariance and autocovariance operators on the sphere (Q2084469) (← links)
- Testing subspace restrictions in the presence of high dimensional nuisance parameters (Q2084475) (← links)
- Large scale tensor regression using kernels and variational inference (Q2102330) (← links)
- Understanding neural networks with reproducing kernel Banach spaces (Q2105111) (← links)
- A review on instance ranking problems in statistical learning (Q2127240) (← links)
- Generalized vec trick for fast learning of pairwise kernel models (Q2127249) (← links)
- \textsf{StreaMRAK} a streaming multi-resolution adaptive kernel algorithm (Q2141175) (← links)
- Neural kernels for recursive support vector regression as a model for episodic memory (Q2165366) (← links)
- Evaluation of statistical relationship of random variables via mutual information (Q2168258) (← links)
- A nonlinear data-driven reduced order model for computational homogenization with physics/pattern-guided sampling (Q2175074) (← links)
- Handling concept drift via model reuse (Q2183593) (← links)
- Efficient spatio-temporal Gaussian regression via Kalman filtering (Q2188275) (← links)
- On the mathematical foundations of stable RKHSs (Q2188280) (← links)
- An efficient method for clustered multi-metric learning (Q2200672) (← links)
- The theory of the quantum kernel-based binary classifier (Q2213171) (← links)
- Quantum-enhanced least-square support vector machine: simplified quantum algorithm and sparse solutions (Q2213246) (← links)
- A unifying representer theorem for inverse problems and machine learning (Q2231644) (← links)
- Kernel variable selection for multicategory support vector machines (Q2237819) (← links)
- A statistical pipeline for identifying physical features that differentiate classes of 3D shapes (Q2245140) (← links)
- The weight-decay technique in learning from data: an optimization point of view (Q2271792) (← links)
- Approximate normalized cuts without eigen-decomposition (Q2282282) (← links)
- Sparse RKHS estimation via globally convex optimization and its application in LPV-IO identification (Q2307599) (← links)
- Variable prioritization in nonlinear black box methods: a genetic association case study (Q2318669) (← links)
- Distribution-free uncertainty quantification for kernel methods by gradient perturbations (Q2320596) (← links)
- Boosting as a kernel-based method (Q2331677) (← links)
- Learning using privileged information: SVM+ and weighted SVM (Q2339396) (← links)
- Premise selection for mathematics by corpus analysis and kernel methods (Q2352489) (← links)
- Learning performance of regularized moving least square regression (Q2359988) (← links)
- Fast rates by transferring from auxiliary hypotheses (Q2361574) (← links)
- A study on three linear discriminant analysis based methods in small sample size problem (Q2384958) (← links)
- Functional reproducing kernel Hilbert spaces for non-point-evaluation functional data (Q2415404) (← links)
- When is there a representer theorem? Nondifferentiable regularisers and Banach spaces (Q2423813) (← links)
- A tutorial on kernel methods for categorization (Q2466900) (← links)
- Tight frame expansions of multiscale reproducing kernels in Sobolev spaces (Q2491722) (← links)
- Consistent identification of Wiener systems: a machine learning viewpoint (Q2628481) (← links)
- Double linear regressions for single labeled image per person face recognition (Q2629788) (← links)
- Generalized semi-inner products with applications to regularized learning (Q2637940) (← links)
- Nonlinear and additive principal component analysis for functional data (Q2657189) (← links)
- Kernel-based methods for Volterra series identification (Q2665176) (← links)
- Deterministic error bounds for kernel-based learning techniques under bounded noise (Q2665700) (← links)
- Convex optimization in sums of Banach spaces (Q2667036) (← links)
- On reproducing kernel Banach spaces: generic definitions and unified framework of constructions (Q2674395) (← links)
- A Riemann-Stein kernel method (Q2676917) (← links)
- Effective dimensionality reduction using kernel locality preserving partial least squares discriminant analysis (Q2699576) (← links)
- (Q2723900) (← links)
- Bayesian Approximate Kernel Regression With Variable Selection (Q3121562) (← links)
- A Generalization of Distinct Representatives and Its Applications (Q3201425) (← links)
- 9 Kernel methods for surrogate modeling (Q3384280) (← links)
- Regularized learning schemes in feature Banach spaces (Q4594821) (← links)
- Variational Gram Functions: Convex Analysis and Optimization (Q4602347) (← links)
