Pages that link to "Item:Q510684"
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The following pages link to Minimax optimal rates of estimation in high dimensional additive models (Q510684):
Displaying 15 items.
- Regularizing Double Machine Learning in Partially Linear Endogenous Models (Q115460) (← links)
- Kernel Knockoffs Selection for Nonparametric Additive Models (Q115586) (← links)
- Minimax optimal estimation in partially linear additive models under high dimension (Q1740526) (← links)
- Oracle posterior contraction rates under hierarchical priors (Q2044331) (← links)
- Stochastic continuum-armed bandits with additive models: minimax regrets and adaptive algorithm (Q2091834) (← links)
- A sieve stochastic gradient descent estimator for online nonparametric regression in Sobolev ellipsoids (Q2105198) (← links)
- Nonparametric distributed learning under general designs (Q2199703) (← links)
- Information based complexity for high dimensional sparse functions (Q2303421) (← links)
- Doubly penalized estimation in additive regression with high-dimensional data (Q2328052) (← links)
- Minimum bias priors for estimating parameters of additive terms in state-space models (Q4841520) (← links)
- Sparse additive machine with ramp loss (Q4995049) (← links)
- An Online Projection Estimator for Nonparametric Regression in Reproducing Kernel Hilbert Spaces (Q6039862) (← links)
- Grouped variable selection with discrete optimization: computational and statistical perspectives (Q6046300) (← links)
- Kernel Ordinary Differential Equations (Q6110694) (← links)
- DDAC-SpAM: A Distributed Algorithm for Fitting High-dimensional Sparse Additive Models with Feature Division and Decorrelation (Q6631694) (← links)
