:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Gregory, Karl B., Nordman, Daniel J.
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Statistics Theory Machine Learning 62J99 (Primary) 62F40 (Secondary)
Accesso online:	https://arxiv.org/abs/2602.02491
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

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

A two-way heterogeneity model for dynamic networks
di: Jiang, Binyan, et al.
Pubblicazione: (2023)

Dimension-free uniform concentration bound for logistic regression
di: Nakakita, Shogo
Pubblicazione: (2024)

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

Inference in pseudo-observation-based regression using (biased) covariance estimation and naive bootstrapping
di: Mack, Simon, et al.
Pubblicazione: (2025)

On the super-efficiency and robustness of the least squares of depth-trimmed regression estimator
di: Zuo, Yijun, et al.
Pubblicazione: (2025)

Choosing observation operators to mitigate model error in Bayesian inverse problems
di: Cvetković, Nada, et al.
Pubblicazione: (2023)

Sparse maximum likelihood estimation for regression models
di: Tsao, Min
Pubblicazione: (2024)

Regularized least squares learning with heavy-tailed noise is minimax optimal
di: Mollenhauer, Mattes, et al.
Pubblicazione: (2025)

Subspace decompositions for association structure learning in multivariate categorical response regression
di: Zhao, Hongru, et al.
Pubblicazione: (2024)

A Bayesian approach to functional regression: theory and computation
di: Berrendero, José R., et al.
Pubblicazione: (2023)

Near-Efficient and Non-Asymptotic Multiway Inference
di: López, Oscar, et al.
Pubblicazione: (2025)

A Latent-Variable Formulation of the Poisson Canonical Polyadic Tensor Model: Maximum Likelihood Estimation and Fisher Information
di: Llosa-Vite, Carlos, et al.
Pubblicazione: (2025)

Poisson Regression in one Covariate on Massive Data
di: Reuter, Torsten, et al.
Pubblicazione: (2024)

Asymptotic Distribution of Low-Dimensional Patterns Induced by Non-Differentiable Regularizers under General Loss Functions
di: Hejný, Ivan, et al.
Pubblicazione: (2025)

Projection predictive variable selection for discrete response families with finite support
di: Weber, Frank, et al.
Pubblicazione: (2023)

Criterion for the resemblance between the mother and the model distribution
di: Sheena, Yo
Pubblicazione: (2022)

MLE convergence speed to information projection of exponential family: Criterion for model dimension and sample size -- complete proof version--
di: Sheena, Yo
Pubblicazione: (2021)

Unbiased estimation and asymptotically valid inference in multivariable Mendelian randomization with many weak instrumental variables
di: Yang, Yihe, et al.
Pubblicazione: (2023)

Bayesian inference of covariate-parameter relationships for population modelling
di: Lie, Han Cheng
Pubblicazione: (2024)

Pathological Regularization Regimes in Classification Tasks
di: Wiesmann, Maximilian, et al.
Pubblicazione: (2024)

Finite sample expansions and risk bounds in high-dimensional SLS models
di: Spokoiny, Vladimir
Pubblicazione: (2024)

Sparse factor models of high dimension
di: Poignard, Benjamin, et al.
Pubblicazione: (2023)

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

Fast Mixing of Data Augmentation Algorithms: Bayesian Probit, Logit, and Lasso Regression
di: Lee, Holden, et al.
Pubblicazione: (2024)

Local asymptotics of selection models with applications in Bayesian selective inference
di: Rasines, Daniel G., et al.
Pubblicazione: (2023)

Stable and consistent density-based clustering via multiparameter persistence
di: Rolle, Alexander, et al.
Pubblicazione: (2020)

On Finite Time Span Estimators of Parameters for Ornstein-Uhlenbeck Processes
di: Han, Jun S., et al.
Pubblicazione: (2025)

Bootstrapping Estimators based on the Block Maxima Method
di: Bücher, Axel, et al.
Pubblicazione: (2024)

Semi-supervised linear regression with missing covariates
di: Risebrow, Benedict M., et al.
Pubblicazione: (2026)

Consistency of M-estimators for non-identically distributed data: the case of fixed-design distributional regression
di: Bücher, Axel, et al.
Pubblicazione: (2025)

Horospherical Depth and Busemann Median on Hadamard Manifolds
di: Jiang, Yangdi, et al.
Pubblicazione: (2026)

Bernstein-von Mises Theorem for Sparse Generalized Linear Model
di: Li, Hanqing, et al.
Pubblicazione: (2026)

A method for sparse and robust independent component analysis
di: Heinonen, Lauri, et al.
Pubblicazione: (2025)

A Bootstrap Test for Independence of Time Series Based on the Distance Covariance
di: Betken, Annika, et al.
Pubblicazione: (2021)

Deep neural networks with dependent weights: Gaussian Process mixture limit, heavy tails, sparsity and compressibility
di: Lee, Hoil, et al.
Pubblicazione: (2022)

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

Near optimal sample complexity for matrix and tensor normal models via geodesic convexity
di: Franks, Cole, et al.
Pubblicazione: (2021)

Bootstrapping not under the null?
di: Derumigny, Alexis, et al.
Pubblicazione: (2025)

Causal Q-Aggregation for CATE Model Selection
di: Lan, Hui, et al.
Pubblicazione: (2023)