The following pages link to (Q3148817):
Displaying 50 items.
- (Q4633012) (← links)
- (Q4636971) (← links)
- (Q4636973) (← links)
- (Q4636981) (← links)
- Kernel partial least squares for stationary data (Q4637047) (← links)
- Nyström subsampling method for coefficient-based regularized regression (Q4968314) (← links)
- (Q4969158) (← links)
- Semi-parametric adjustment to computer models (Q4987231) (← links)
- (Q4998934) (← links)
- (Q4998938) (← links)
- Multikernel Regression with Sparsity Constraint (Q4999353) (← links)
- Linearly Constrained Linear Quadratic Regulator from the Viewpoint of Kernel Methods (Q5009773) (← links)
- An Epigraphical Approach to the Representer Theorem (Q5026403) (← links)
- Kernel partial correlation: a novel approach to capturing conditional independence in graphical models for noisy data (Q5036378) (← links)
- Boltzmann–Gibbs Random Fields with Mesh-free Precision Operators Based on Smoothed Particle Hydrodynamics (Q5047940) (← links)
- (Q5053180) (← links)
- (Q5053232) (← links)
- (Q5053296) (← links)
- (Q5053305) (← links)
- Parameter choices for sparse regularization with the ℓ1 norm <sup>*</sup> (Q5060748) (← links)
- Semi-Infinite Linear Regression and Its Applications (Q5071432) (← links)
- What Kinds of Functions Do Deep Neural Networks Learn? Insights from Variational Spline Theory (Q5071660) (← links)
- A scalable approximate Bayesian inference for high-dimensional Gaussian processes (Q5095985) (← links)
- On Kernel Method–Based Connectionist Models and Supervised Deep Learning Without Backpropagation (Q5131164) (← links)
- Convergence of Gaussian Process Regression with Estimated Hyper-Parameters and Applications in Bayesian Inverse Problems (Q5139353) (← links)
- A Statistical Method for Emulation of Computer Models With Invariance-Preserving Properties, With Application to Structural Energy Prediction (Q5146033) (← links)
- On the Improved Rates of Convergence for Matérn-Type Kernel Ridge Regression with Application to Calibration of Computer Models (Q5149775) (← links)
- Data-Driven Modeling for Wave-Propagation (Q5152865) (← links)
- (Q5214198) (← links)
- Generalized support vector regression: Duality and tensor-kernel representation (Q5220070) (← links)
- On Representer Theorems and Convex Regularization (Q5231664) (← links)
- Adjustments to Computer Models via Projected Kernel Calibration (Q5237166) (← links)
- Robust Support Vector Machines for Classification with Nonconvex and Smooth Losses (Q5380444) (← links)
- Generalized Mercer Kernels and Reproducing Kernel Banach Spaces (Q5383917) (← links)
- (Q5843090) (← links)
- Frames, their relatives and reproducing kernel Hilbert spaces (Q5870277) (← links)
- Kernel and Dissimilarity Methods for Exploratory Analysis in a Social Context (Q5871032) (← links)
- Penalized Projected Kernel Calibration for Computer Models (Q5880618) (← links)
- An Online Projection Estimator for Nonparametric Regression in Reproducing Kernel Hilbert Spaces (Q6039862) (← links)
- A multi-birth metric learning framework based on binary constraints (Q6052417) (← links)
- On the Inconsistency of Kernel Ridgeless Regression in Fixed Dimensions (Q6070298) (← links)
- A nonlinear kernel SVM Classifier via \(L_{0/1}\) soft-margin loss with classification performance (Q6073171) (← links)
- Superoscillations and Fock spaces (Q6080746) (← links)
- Reproducing kernel Hilbert spaces in the mean field limit (Q6095750) (← links)
- Sparse machine learning in Banach spaces (Q6106931) (← links)
- A Reproducing Kernel Hilbert Space Approach to Functional Calibration of Computer Models (Q6109971) (← links)
- A new classifier for imbalanced data based on a generalized density ratio model (Q6113642) (← links)
- Accelerating metabolic models evaluation with statistical metamodels: application to <i>Salmonella</i> infection models (Q6127059) (← links)
- Unified SVM algorithm based on LS-DC loss (Q6134358) (← links)
- Learning system parameters from Turing patterns (Q6134365) (← links)
