Pages that link to "Item:Q1847952"

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

Displaying 50 items.

• Nonparametric regression estimation with general parametric error covariance (Q1000563) (← links)
• Learning near-optimal policies with Bellman-residual minimization based fitted policy iteration and a single sample path (Q1009248) (← links)
• Consistency of support vector machines for forecasting the evolution of an unknown ergodic dynamical system from observations with unknown noise (Q1020982) (← links)
• Principles of nonparametric learning. Papers from the summer school, Udine, Italy, July 9--13, 2001 (Q1407941) (← links)
• A bound on the expected maximal deviation of averages from their means. (Q1423255) (← links)
• Estimation of the optimal design of a nonlinear parametric regression problem via Monte Carlo experiments (Q1621200) (← links)
• Stochastic \(L^1\)-optimal control via forward and backward sampling (Q1624907) (← links)
• Nonparametric regression using needlet kernels for spherical data (Q1633627) (← links)
• Universal discretization (Q1635842) (← links)
• A nearest neighbor estimate of the residual variance (Q1639197) (← links)
• Uniform in bandwidth consistency of nonparametric regression based on copula representation (Q1640948) (← links)
• Variational multiscale nonparametric regression: smooth functions (Q1650131) (← links)
• Prediction of dynamical time series using kernel based regression and smooth splines (Q1657952) (← links)
• Conditional quantile estimation based on optimal quantization: from theory to practice (Q1663189) (← links)
• Variance reduction for discretised diffusions via regression (Q1674395) (← links)
• On a near optimal sampling strategy for least squares polynomial regression (Q1674720) (← links)
• Orthogonal series estimates on strong spatial mixing data (Q1681044) (← links)
• On estimation of surrogate models for multivariate computer experiments (Q1733118) (← links)
• Data depth for measurable noisy random functions (Q1733273) (← links)
• Nonparametric quantile estimation using importance sampling (Q1744716) (← links)
• Slice inverse regression with score functions (Q1753150) (← links)
• A new method for bounding rates of convergence of empirical spectral distributions (Q1770906) (← links)
• Bandwidth choice for nonparametric classification (Q1781162) (← links)
• A note on estimating the conditional expectation under censoring and association: strong uniform consistency (Q1785812) (← links)
• Regression function and noise variance tracking methods for data streams with concept drift (Q1797885) (← links)
• Estimate hand poses efficiently from single depth images (Q1800015) (← links)
• Smooth fixed volume discrepancy, dispersion, and related problems (Q1801178) (← links)
• On cross-validation in kernel and partitioning regression estimation. (Q1871263) (← links)
• How well can a regression function be estimated if the distribution of the (random) design is concentrated on a finite set? (Q1877843) (← links)
• Shape restricted nonparametric regression with Bernstein polynomials (Q1927049) (← links)
• Analysis of convergence performance of neural networks ranking algorithm (Q1942699) (← links)
• Optimal regression rates for SVMs using Gaussian kernels (Q1951100) (← links)
• General oracle inequalities for model selection (Q1951973) (← links)
• Dimension reduction for regression estimation with nearest neighbor method (Q1952062) (← links)
• Robust regression through the Huber's criterion and adaptive lasso penalty (Q1952217) (← links)
• Minimax semi-supervised set-valued approach to multi-class classification (Q1983613) (← links)
• Over-parametrized deep neural networks minimizing the empirical risk do not generalize well (Q1983625) (← links)
• A ridge estimator of the drift from discrete repeated observations of the solution of a stochastic differential equation (Q1983630) (← links)
• Rho-estimators revisited: general theory and applications (Q1990601) (← links)
• The mean shift algorithm and its relation to kernel regression (Q1991846) (← links)
• Stratified regression-based variance reduction approach for weak approximation schemes (Q1996942) (← links)
• Multivariate adaptive warped kernel estimation (Q2002571) (← links)
• A regression-based smoothing spline Monte Carlo algorithm for pricing American options in discrete time (Q2006839) (← links)
• Kernel classification with missing data and the choice of smoothing parameters (Q2010808) (← links)
• On classification with nonignorable missing data (Q2034467) (← links)
• On universal algorithms for classifying and predicting stationary processes (Q2039763) (← links)
• Linearized two-layers neural networks in high dimension (Q2039801) (← links)
• High-dimensional index volatility models via Stein's identity (Q2040038) (← links)
• Estimation of an improved surrogate model in uncertainty quantification by neural networks (Q2042433) (← links)
• Estimating multi-index models with response-conditional least squares (Q2044313) (← links)