Pages that link to "Item:Q2788410"
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The following pages link to Divide and conquer kernel ridge regression: a distributed algorithm with minimax optimal rates (Q2788410):
Displaying 50 items.
- A partially linear framework for massive heterogeneous data (Q309709) (← links)
- Distributed regression learning with coefficient regularization (Q1645155) (← links)
- Distributed testing and estimation under sparse high dimensional models (Q1650081) (← links)
- Distributed kernel-based gradient descent algorithms (Q1745365) (← links)
- Randomized sketches for kernel CCA (Q1982398) (← links)
- Distributed regularized least squares with flexible Gaussian kernels (Q2036424) (← links)
- Distributed linear regression by averaging (Q2039793) (← links)
- Learning sparse conditional distribution: an efficient kernel-based approach (Q2044348) (← links)
- Distributed networked learning with correlated data (Q2071980) (← links)
- Distributed adaptive Huber regression (Q2076119) (← links)
- Achieving fairness with a simple ridge penalty (Q2080355) (← links)
- From inexact optimization to learning via gradient concentration (Q2111477) (← links)
- Robust distributed estimation and variable selection for massive datasets via rank regression (Q2135513) (← links)
- \textsf{StreaMRAK} a streaming multi-resolution adaptive kernel algorithm (Q2141175) (← links)
- Robust reduced rank regression in a distributed setting (Q2158850) (← links)
- Learning rate of distribution regression with dependent samples (Q2171946) (← links)
- Distributed kernel gradient descent algorithm for minimum error entropy principle (Q2175022) (← links)
- Surface temperature monitoring in liver procurement via functional variance change-point analysis (Q2179949) (← links)
- Theory of deep convolutional neural networks: downsampling (Q2185717) (← links)
- Nonparametric distributed learning under general designs (Q2199703) (← links)
- Distributed learning and distribution regression of coefficient regularization (Q2223571) (← links)
- Spectrally-truncated kernel ridge regression and its free lunch (Q2233553) (← links)
- Robust distributed modal regression for massive data (Q2242003) (← links)
- Robust communication-efficient distributed composite quantile regression and variable selection for massive data (Q2242035) (← links)
- Randomized incomplete \(U\)-statistics in high dimensions (Q2284368) (← links)
- Quantile regression under memory constraint (Q2284373) (← links)
- Quantile regression in big data: a divide and conquer based strategy (Q2291332) (← links)
- Distributed simultaneous inference in generalized linear models via confidence distribution (Q2293540) (← links)
- Projected spline estimation of the nonparametric function in high-dimensional partially linear models for massive data (Q2328064) (← links)
- Distributed learning with multi-penalty regularization (Q2415399) (← links)
- Distributed semi-supervised regression learning with coefficient regularization (Q2668180) (← links)
- Averaging versus voting: a comparative study of strategies for distributed classification (Q2668577) (← links)
- Communication-efficient sparse composite quantile regression for distributed data (Q2696327) (← links)
- Distributed Bayesian posterior voting strategy for massive data (Q2696714) (← links)
- Distributed Generalized Cross-Validation for Divide-and-Conquer Kernel Ridge Regression and Its Asymptotic Optimality (Q3391209) (← links)
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- Distributed learning with partial coefficients regularization (Q4571050) (← links)
- Another Look at Distance-Weighted Discrimination (Q4603806) (← links)
- Bias corrected regularization kernel method in ranking (Q4615656) (← links)
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- Computational Limits of A Distributed Algorithm For Smoothing Spline (Q4637031) (← links)
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- Regularized Nyström subsampling in regression and ranking problems under general smoothness assumptions (Q4968723) (← links)
- WONDER: Weighted one-shot distributed ridge regression in high dimensions (Q4969115) (← links)
