The following pages link to (Q4558172):
Displaying 26 items.
- Distributed kernel-based gradient descent algorithms (Q1745365) (← links)
- Distributed regularized least squares with flexible Gaussian kernels (Q2036424) (← links)
- From inexact optimization to learning via gradient concentration (Q2111477) (← links)
- Optimal learning rates for distribution regression (Q2283125) (← links)
- Distributed estimation of principal eigenspaces (Q2284361) (← links)
- Distributed semi-supervised regression learning with coefficient regularization (Q2668180) (← links)
- Kernel regression, minimax rates and effective dimensionality: Beyond the regular case (Q3298576) (← links)
- Nyström subsampling method for coefficient-based regularized regression (Q4968314) (← links)
- (Q4969157) (← links)
- (Q4969211) (← links)
- (Q4998897) (← links)
- Distributed least squares prediction for functional linear regression* (Q5019925) (← links)
- Distributed spectral pairwise ranking algorithms (Q5060714) (← links)
- (Q5148925) (← links)
- (Q5148996) (← links)
- Convergence analysis of distributed multi-penalty regularized pairwise learning (Q5220068) (← links)
- Distributed learning with indefinite kernels (Q5236752) (← links)
- A review of distributed statistical inference (Q5880109) (← links)
- Spectral algorithms for learning with dependent observations (Q6049257) (← links)
- Distributed SGD in overparametrized linear regression (Q6496338) (← links)
- Distributed robust regression with correntropy losses and regularization kernel networks (Q6564882) (← links)
- Iterative kernel regression with preconditioning (Q6587596) (← links)
- Weighted spectral filters for kernel interpolation on spheres: estimates of prediction accuracy for noisy data (Q6587629) (← links)
- Spectral algorithms for functional linear regression (Q6592232) (← links)
- Radial basis function approximation with distributively stored data on spheres (Q6593033) (← links)
- ORKM: online regularized \(K\)-means clustering for online multi-view data (Q6595308) (← links)
