Copertina

Regularized least squares learning with heavy-tailed noise is minimax optimal

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Mollenhauer, Mattes, Mücke, Nicole, Meunier, Dimitri, Gretton, Arthur
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Statistics Theory 62G08 (Primary) 62G35, 62J07 (Secondary)
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

On deviation probabilities in non-parametric regression with heavy-tailed noise
di: Ben-Hamou, Anna, et al.
Pubblicazione: (2023)

Robust Estimation in Finite Mixture Models
di: Lecestre, Alexandre
Pubblicazione: (2021)

Non-asymptotic analysis of the performance of the penalized least trimmed squares in sparse models
di: Zuo, Yijun
Pubblicazione: (2025)

Composite Lp-quantile regression, near quantile regression and the oracle model selection theory
di: Mou, Fuming Lin WEilin
Pubblicazione: (2025)

Mode-based estimation of the center of symmetry
di: Chacón, José E., et al.
Pubblicazione: (2024)

Robust density estimation with the $\mathbb{L}_{1}$-loss. Applications to the estimation of a density on the line satisfying a shape constraint
di: Baraud, Y., et al.
Pubblicazione: (2022)

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

Rejoinder to the discussion of "Mode-based estimation of the center of symmetry"
di: Chacón, José E., et al.
Pubblicazione: (2025)

Tuning free Catoni type joint robust estimation
di: Li, Xiang, et al.
Pubblicazione: (2025)

Quick and Simple Kernel Differential Equation Regression Estimators for Data with Sparse Design
di: Ge, Chunlei, et al.
Pubblicazione: (2024)

Rates of convergence for nearest neighbor estimators with the smoother regression function
di: Ayano, Takanori
Pubblicazione: (2011)

Quadratic functional estimation from observations with multiplicative measurement error
di: Neubert, Bianca, et al.
Pubblicazione: (2024)

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

Adaptive exact recovery in sparse nonparametric models
di: Stepanova, Natalia, et al.
Pubblicazione: (2024)

Adaptive almost full recovery in sparse nonparametric models
di: Stepanova, Natalia, et al.
Pubblicazione: (2025)

Strong consistency of the local linear estimator for a generalized regression function with dependent functional data
di: Matsuoka, Danilo Hiroshi, et al.
Pubblicazione: (2026)

Exact variable selection in sparse nonparametric models
di: Stepanova, Natalia, et al.
Pubblicazione: (2023)

Large sample behavior of the least trimmed squares estimator
di: Zuo, Yijun
Pubblicazione: (2022)

Efficient Inference on High-Dimensional Linear Models with Missing Outcomes
di: Zhang, Yikun, et al.
Pubblicazione: (2023)

The minimax optimal convergence rate of posterior density in the weighted orthogonal polynomials
di: Luo, Yiqi, et al.
Pubblicazione: (2026)

Conditional Outcome Equivalence: A Quantile Alternative to CATE
di: Givens, Josh, et al.
Pubblicazione: (2024)

Batch learning equals online learning in Bayesian supervised learning
di: Lê, Hông Vân
Pubblicazione: (2025)

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

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

A kernel-based framework for covariate significance tests in nonparametric regression
di: Diz-Castro, Daniel, et al.
Pubblicazione: (2025)

On the optimal prediction of extreme events in heavy-tailed time series with applications to solar flare forecasting
di: Verma, Victor, et al.
Pubblicazione: (2024)

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

Maximum smoothed likelihood method for the combination of multiple diagnostic tests, with application to the ROC estimation
di: Zheng, Fangyong, et al.
Pubblicazione: (2026)

A hybrid-Hill estimator enabled by heavy-tailed block maxima
di: Neves, Claudia, et al.
Pubblicazione: (2025)

Is model selection possible for the $\ell_p$-loss? PCO estimation for regression models
di: Lacour, Claire, et al.
Pubblicazione: (2025)

Lower Bounds for Nonparametric Estimation of Ordinary Differential Equations
di: Schötz, Christof, et al.
Pubblicazione: (2024)

Bagging cross-validated bandwidths with application to Big Data
di: Barreiro-Ures, Daniel, et al.
Pubblicazione: (2024)

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

Localizing differences in smooths with simultaneous confidence bounds on the true discovery proportion
di: Swanson, David
Pubblicazione: (2020)

Frontiers to the learning of nonparametric hidden Markov models
di: Abraham, Kweku, et al.
Pubblicazione: (2023)

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

Asymptotic e-processes
di: Massiani, Pierre-François, et al.
Pubblicazione: (2026)

Distributional Convergence of Empirical Entropic Optimal Transport and Statistical Applications
di: Arenas-Velilla, Santiago, et al.
Pubblicazione: (2026)

A Note on Minimax Robustness of Designs Against Correlated or Heteroscedastic Responses
di: Wiens, Douglas P.
Pubblicazione: (2023)

To ignore dependencies is perhaps not a sin
di: Wiens, Douglas P.
Pubblicazione: (2024)