Pages that link to "Item:Q2012925"
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The following pages link to Randomized sketches for kernels: fast and optimal nonparametric regression (Q2012925):
Displaying 34 items.
- Vecchia-Laplace approximations of generalized Gaussian processes for big non-Gaussian spatial data (Q830598) (← links)
- Kernel conjugate gradient methods with random projections (Q1979923) (← links)
- Randomized sketches for kernel CCA (Q1982398) (← links)
- Approximate nonparametric quantile regression in reproducing kernel Hilbert spaces via random projection (Q2056283) (← links)
- Consistent online Gaussian process regression without the sample complexity bottleneck (Q2058904) (← links)
- Approximate kernel PCA: computational versus statistical trade-off (Q2105193) (← links)
- Functional principal subspace sampling for large scale functional data analysis (Q2137809) (← links)
- From Gauss to Kolmogorov: localized measures of complexity for ellipses (Q2199701) (← links)
- Nonparametric distributed learning under general designs (Q2199703) (← links)
- Spectrally-truncated kernel ridge regression and its free lunch (Q2233553) (← links)
- On nonparametric randomized sketches for kernels with further smoothness (Q2322682) (← links)
- Concentration of kernel matrices with application to kernel spectral clustering (Q2656607) (← links)
- On b-bit min-wise hashing for large-scale regression and classification with sparse data (Q4558503) (← links)
- Faster Kernel Ridge Regression Using Sketching and Preconditioning (Q4588937) (← links)
- (Q4969055) (← links)
- (Q4969158) (← links)
- (Q4969263) (← links)
- Efficient kernel-based variable selection with sparsistency (Q5037806) (← links)
- Disentangled Representation Learning and Generation With Manifold Optimization (Q5044168) (← links)
- Smoothing Splines Approximation Using Hilbert Curve Basis Selection (Q5057090) (← links)
- (Q5148925) (← links)
- More efficient estimation for logistic regression with optimal subsamples (Q5214224) (← links)
- Distributed learning for sketched kernel regression (Q6079133) (← links)
- Distributed Bayesian inference in massive spatial data (Q6111472) (← links)
- Decentralized learning over a network with Nyström approximation using SGD (Q6117024) (← links)
- On the coercivity condition in the learning of interacting particle systems (Q6151507) (← links)
- Optimally tackling covariate shift in RKHS-based nonparametric regression (Q6172197) (← links)
- Low-rank approximation for smoothing spline via eigensystem truncation (Q6541765) (← links)
- Sparse multiple kernel learning: minimax rates with random projection (Q6541942) (← links)
- Deterministic subsampling for logistic regression with massive data (Q6567421) (← links)
- Robust and efficient subsampling algorithms for massive data logistic regression (Q6579821) (← links)
- Spectral regularized Kernel two-sample tests (Q6608681) (← links)
- A Subsampling Method for Regression Problems Based on Minimum Energy Criterion (Q6631125) (← links)
- Optimal policy evaluation using kernel-based temporal difference methods (Q6656605) (← links)
