Pages that link to "Item:Q1847952"

The following pages link to A distribution-free theory of nonparametric regression (Q1847952):

Displaying 50 items.

• Estimation of a density using an improved surrogate model (Q2044316) (← links)
• Consistent regression using data-dependent coverings (Q2044358) (← links)
• Strongly universally consistent nonparametric regression and classification with privatised data (Q2044383) (← links)
• On a Nadaraya-Watson estimator with two bandwidths (Q2044390) (← links)
• On histogram-based regression and classification with incomplete data (Q2044763) (← links)
• Solving the Kolmogorov PDE by means of deep learning (Q2051092) (← links)
• Universal Bayes consistency in metric spaces (Q2054482) (← links)
• On the rate of convergence of fully connected deep neural network regression estimates (Q2054491) (← links)
• Adaptive learning rates for support vector machines working on data with low intrinsic dimension (Q2073699) (← links)
• Marginal singularity and the benefits of labels in covariate-shift (Q2073708) (← links)
• Function approximation by deep neural networks with parameters \(\{0, \pm \frac{1}{2}, \pm 1,2\}\) (Q2074650) (← links)
• The dependent Dirichlet process and related models (Q2075788) (← links)
• On the rate of convergence of image classifiers based on convolutional neural networks (Q2087403) (← links)
• Bootstrap robust prescriptive analytics (Q2089765) (← links)
• Exact minimax risk for linear least squares, and the lower tail of sample covariance matrices (Q2091833) (← links)
• A minimax framework for quantifying risk-fairness trade-off in regression (Q2091849) (← links)
• Classifying and explaining defects with small data for the semiconductor industry (Q2094849) (← links)
• Models under which random forests perform badly; consequences for applications (Q2095717) (← links)
• Understanding neural networks with reproducing kernel Banach spaces (Q2105111) (← links)
• Bounds on the conditional and average treatment effect with unobserved confounding factors (Q2105186) (← links)
• A sieve stochastic gradient descent estimator for online nonparametric regression in Sobolev ellipsoids (Q2105198) (← links)
• Dependence of variance on covariate design in nonparametric link regression (Q2105389) (← links)
• Random forest estimation of conditional distribution functions and conditional quantiles (Q2106811) (← links)
• Suboptimality of constrained least squares and improvements via non-linear predictors (Q2108490) (← links)
• Variance reduction for additive functionals of Markov chains via martingale representations (Q2114045) (← links)
• On least squares estimation under heteroscedastic and heavy-tailed errors (Q2119229) (← links)
• Canonical thresholding for nonsparse high-dimensional linear regression (Q2119237) (← links)
• Concentration inequalities for cross-validation in scattered data approximation (Q2120815) (← links)
• Estimation of conditional distribution functions from data with additional errors applied to shape optimization (Q2121427) (← links)
• Data-driven discovery of emergent behaviors in collective dynamics (Q2127368) (← links)
• Approximations of conditional probability density functions in Lebesgue spaces via mixture of experts models (Q2129248) (← links)
• Aggregated hold out for sparse linear regression with a robust loss function (Q2136632) (← links)
• Sampling discretization and related problems (Q2136857) (← links)
• Learning with tree tensor networks: complexity estimates and model selection (Q2137001) (← links)
• A fuzzy nonlinear univariate regression model with exact predictors and fuzzy responses (Q2157070) (← links)
• Learning interaction kernels in stochastic systems of interacting particles from multiple trajectories (Q2162118) (← links)
• Distributed learning via filtered hyperinterpolation on manifolds (Q2162123) (← links)
• Multiscale regression on unknown manifolds (Q2167604) (← links)
• \(k\)NN estimation in functional partial linear modeling (Q2175665) (← links)
• A simple approach to construct confidence bands for a regression function with incomplete data (Q2176328) (← links)
• Connections between numerical integration, discrepancy, dispersion, and universal discretization (Q2178666) (← links)
• Solving linear parabolic rough partial differential equations (Q2190037) (← links)
• Just interpolate: kernel ``ridgeless'' regression can generalize (Q2196223) (← links)
• Nonparametric regression using deep neural networks with ReLU activation function (Q2215715) (← links)
• Minimax optimal rates for Mondrian trees and forests (Q2215734) (← links)
• Discrete-type approximations for non-Markovian optimal stopping problems. II (Q2218844) (← links)
• Risk of estimators for Sobol' sensitivity indices based on metamodels (Q2219226) (← links)
• Estimating covariance and precision matrices along subspaces (Q2219236) (← links)
• Analysis of the rate of convergence of fully connected deep neural network regression estimates with smooth activation function (Q2222227) (← links)
• Kernel density estimates in a non-standard situation (Q2223170) (← links)