Cover Image

Adaptive Geometric Regression for High-Dimensional Structured Data

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gajer, Pawel, Ravel, Jacques
Format:	Preprint
Published:	2025
Subjects:	Methodology Statistics Theory 62G08, 62G20, 05C50, 58J35
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

From Global to Local Correlation: Geometric Decomposition of Statistical Inference
by: Gajer, Pawel, et al.
Published: (2025)

Mean and Covariance Estimation for Discretely Observed High-Dimensional Functional Data: Rates of Convergence and Division of Observational Regimes
by: Petersen, Alexander
Published: (2024)

Variable Selection for Additive Global Fréchet Regression
by: Yang, Haoyi, et al.
Published: (2025)

Nonparametric Regression for Random Unbiased Perturbations
by: Lyubarskaja, Anna, et al.
Published: (2025)

Sparse semiparametric regression when predictors are mixture of functional and high-dimensional variables
by: Novo, Silvia, et al.
Published: (2024)

A Minimax Theory of Nonparametric Regression Under Covariate Shift
by: Zamolodtchikov, Petr
Published: (2026)

Spectral Bayesian Regression on the Sphere
by: Durastanti, Claudio
Published: (2026)

A Bernstein polynomial approach for the estimation of cumulative distribution functions in the presence of missing data
by: Gharbi, Rihab, et al.
Published: (2025)

Adaptive Kernel Regression for Constrained Route Alignment: Theory and Iterative Data Sharpening
by: Du, Shiyin, et al.
Published: (2026)

Harmonic Map Regression: Rate-Optimal Nonparametric Estimation on Manifolds with Topological Recovery
by: Chen, Xiaoyu
Published: (2026)

Automatic and location-adaptive estimation in functional single-index regression
by: Novo, Silvia, et al.
Published: (2024)

Adaptation using spatially distributed Gaussian Processes
by: Szabo, Botond, et al.
Published: (2023)

Estimating a regression function under possible heteroscedastic and heavy-tailed errors. Application to shape-restricted regression
by: Baraud, Yannick, et al.
Published: (2025)

Dirichlet kernel density estimation on the simplex with missing data
by: Daayeb, Hanen, et al.
Published: (2026)

Average Marginal Effects in One-Step Partially Linear Instrumental Regressions
by: Girard, Lucas, et al.
Published: (2026)

Inference with Mondrian Random Forests
by: Cattaneo, Matias D., et al.
Published: (2023)

Minimax And Adaptive Transfer Learning for Nonparametric Classification under Distributed Differential Privacy Constraints
by: Auddy, Arnab, et al.
Published: (2024)

Semi-functional partial linear regression with measurement error: An approach based on $k$NN estimation
by: Novo, Silvia, et al.
Published: (2024)

Nonparametric Empirical Bayes Estimation on Heterogeneous Data
by: Banerjee, Trambak, et al.
Published: (2020)

Asymptotic confidence bands for the histogram regression estimator
by: Neumeyer, Natalie, et al.
Published: (2025)

Distributional Conformal Prediction for Markov Processes
by: Dai, Dehao, et al.
Published: (2026)

Adaptive inference over Besov spaces in the white noise model using $p$-exponential priors
by: Agapiou, Sergios, et al.
Published: (2022)

Multiple Imputation Methods under Extreme Values
by: Brasil, Enzo Porto
Published: (2026)

Factor Informed Double Deep Learning For Average Treatment Effect Estimation
by: Fan, Jianqing, et al.
Published: (2025)

On the Dirichlet-kernel Gasser--Müller estimator and its competitors for fixed design regression on the simplex
by: Daayeb, Hanen, et al.
Published: (2025)

Estimation of a Likelihood Ratio Ordered Family of Distributions
by: Mösching, Alexandre, et al.
Published: (2020)

Local linear smoothing for regression surfaces on the simplex using Dirichlet kernels
by: Genest, Christian, et al.
Published: (2024)

Discriminating Tail Behavior Using Halfspace Depths: Population and Empirical Perspectives
by: Singha, Sibsankar, et al.
Published: (2025)

Estimation of the invariant measure of a multidimensional diffusion from noisy observations
by: Maillet, Raphaël, et al.
Published: (2024)

Semiparametric Uncertainty Quantification via Isotonized Posterior for Deconvolutions
by: Gili, Francesco, et al.
Published: (2026)

Functional Partial Least-Squares: Adaptive Estimation and Inference
by: Babii, Andrii, et al.
Published: (2024)

Deep learning with missing data
by: Ma, Tianyi, et al.
Published: (2025)

Totally Concave Regression
by: Ki, Dohyeong, et al.
Published: (2025)

Convergence rates of non-stationary and deep Gaussian process regression
by: Osborne, Conor, et al.
Published: (2023)

Robust Tail Index Estimation under Random Censoring via Minimum Density Power Divergence
by: Guesmia, Nour Elhouda, et al.
Published: (2025)

Robust and Smooth Estimation of the Extreme Tail Index via Weighted Minimum Density Power Divergence
by: Mancer, Saida, et al.
Published: (2025)

Importance sampling for Sobol' indices estimation
by: Boucharif, Haythem, et al.
Published: (2025)

Demystifying Functional Random Forests: Novel Explainability Tools for Model Transparency in High-Dimensional Spaces
by: Maturo, Fabrizio, et al.
Published: (2024)

Generative Modelling via Quantile Regression
by: Schmidt-Hieber, Johannes, et al.
Published: (2024)

Identifying arbitrary transformation between the slopes in scalar-on-function regression
by: Niyogi, Pratim Guha, et al.
Published: (2024)