Pages that link to "Item:Q5405123"

The following pages link to Minimax-optimal rates for sparse additive models over kernel classes via convex programming (Q5405123):

Displaying 50 items.

• Regression in Tensor Product Spaces by the Method of Sieves (Q104871) (← links)
• Kernel Knockoffs Selection for Nonparametric Additive Models (Q115586) (← links)
• Fast learning rate of multiple kernel learning: trade-off between sparsity and smoothness (Q366980) (← links)
• Cross-validation for selecting a model selection procedure (Q494374) (← links)
• Tight conditions for consistency of variable selection in the context of high dimensionality (Q741803) (← links)
• Entropy and sampling numbers of classes of ridge functions (Q745852) (← links)
• Approximation properties of certain operator-induced norms on Hilbert spaces (Q765689) (← links)
• Statistical inference in sparse high-dimensional additive models (Q820814) (← links)
• A reproducing kernel Hilbert space approach to high dimensional partially varying coefficient model (Q830540) (← links)
• Fast learning rate of non-sparse multiple kernel learning and optimal regularization strategies (Q1657947) (← links)
• Error analysis for coefficient-based regularized regression in additive models (Q1698243) (← links)
• Minimax optimal estimation in partially linear additive models under high dimension (Q1740526) (← links)
• Oracle inequalities for sparse additive quantile regression in reproducing kernel Hilbert space (Q1750287) (← links)
• Detection of sparse additive functions (Q1950867) (← links)
• PAC-Bayesian estimation and prediction in sparse additive models (Q1951111) (← links)
• Optimal prediction for high-dimensional functional quantile regression in reproducing kernel Hilbert spaces (Q1979424) (← links)
• Randomized sketches for kernel CCA (Q1982398) (← links)
• Empirical Bayes oracle uncertainty quantification for regression (Q1996760) (← links)
• The recovery of ridge functions on the hypercube suffers from the curse of dimensionality (Q1996887) (← links)
• Learning general sparse additive models from point queries in high dimensions (Q2007617) (← links)
• Variable selection consistency of Gaussian process regression (Q2054515) (← links)
• Approximate nonparametric quantile regression in reproducing kernel Hilbert spaces via random projection (Q2056283) (← links)
• Penalized kernel quantile regression for varying coefficient models (Q2059422) (← links)
• Stochastic continuum-armed bandits with additive models: minimax regrets and adaptive algorithm (Q2091834) (← links)
• Extreme eigenvalues of nonlinear correlation matrices with applications to additive models (Q2145814) (← links)
• Nonparametric distributed learning under general designs (Q2199703) (← links)
• Adaptive variable selection in nonparametric sparse regression (Q2253981) (← links)
• Information based complexity for high dimensional sparse functions (Q2303421) (← links)
• Discovering model structure for partially linear models (Q2304237) (← links)
• On nonparametric randomized sketches for kernels with further smoothness (Q2322682) (← links)
• Rates of contraction with respect to \(L_2\)-distance for Bayesian nonparametric regression (Q2326065) (← links)
• Doubly penalized estimation in additive regression with high-dimensional data (Q2328052) (← links)
• Minimax-optimal nonparametric regression in high dimensions (Q2343958) (← links)
• Sparse high-dimensional varying coefficient model: nonasymptotic minimax study (Q2352741) (← links)
• A unified penalized method for sparse additive quantile models: an RKHS approach (Q2409400) (← links)
• Statistical inference in compound functional models (Q2447291) (← links)
• Zeroth-order nonconvex stochastic optimization: handling constraints, high dimensionality, and saddle points (Q2696568) (← links)
• Learning rates for the risk of kernel-based quantile regression estimators in additive models (Q2805231) (← links)
• A semiparametric model for matrix regression (Q3385484) (← links)
• Metamodel construction for sensitivity analysis (Q4606427) (← links)
• Multiple Kernel Learningの学習理論 (Q5011460) (← links)
• (Q5054581) (← links)
• Improved Estimation of High-dimensional Additive Models Using Subspace Learning (Q5057096) (← links)
• Nonlinear Variable Selection via Deep Neural Networks (Q5066407) (← links)
• Hierarchical Total Variations and Doubly Penalized ANOVA Modeling for Multivariate Nonparametric Regression (Q5066471) (← links)
• Bayesian Model Selection in Additive Partial Linear Models Via Locally Adaptive Splines (Q5084431) (← links)
• Kernel Meets Sieve: Post-Regularization Confidence Bands for Sparse Additive Model (Q5146054) (← links)
• Automatic Component Selection in Additive Modeling of French National Electricity Load Forecasting (Q5280089) (← links)
• High-Dimensional Feature Selection by Feature-Wise Kernelized Lasso (Q5378315) (← links)
• The Lasso for High Dimensional Regression with a Possible Change Point (Q5743231) (← links)