:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Ghosh, Shubhangi, Guo, Yilin, Weng, Haolei, Maleki, Arian
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Statistics Theory
Accesso online:	https://arxiv.org/abs/2501.13323
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

A note on the minimax risk of sparse linear regression
di: Guo, Yilin, et al.
Pubblicazione: (2024)

Signal-to-noise ratio aware minimaxity and higher-order asymptotics
di: Guo, Yilin, et al.
Pubblicazione: (2022)

A minimax optimal approach to high-dimensional double sparse linear regression
di: Zhang, Yanhang, et al.
Pubblicazione: (2023)

Is speckle noise more challenging to mitigate than additive noise?
di: Malekian, Reihaneh, et al.
Pubblicazione: (2024)

Sharp Bounds for Multiple Models in Matrix Completion
di: Liu, Dali, et al.
Pubblicazione: (2024)

Minimax Analysis of Estimation Problems in Coherent Imaging
di: Xing, Hao, et al.
Pubblicazione: (2025)

Sharp minimax risks and phase transitions in sparse submatrix detection
di: Goswami, Subhajit, et al.
Pubblicazione: (2026)

On the effect of noise on fitting linear regression models
di: Ullah, Insha, et al.
Pubblicazione: (2024)

Characterizing the minimax rate of nonparametric regression under bounded star-shaped constraints
di: Prasadan, Akshay, et al.
Pubblicazione: (2024)

Infinitely divisible privacy and beyond I: resolution of the $s^2=2k$ conjecture
di: Pandey, Aaradhya, et al.
Pubblicazione: (2025)

Detection and inference of changes in high-dimensional linear regression with non-sparse structures
di: Cho, Haeran, et al.
Pubblicazione: (2024)

Fitting sparse high-dimensional varying-coefficient models with Bayesian regression tree ensembles
di: Ghosh, Soham, et al.
Pubblicazione: (2025)

Robust Unsupervised Multi-task and Transfer Learning on Gaussian Mixture Models
di: Tian, Ye, et al.
Pubblicazione: (2022)

Theoretical Analysis of Leave-one-out Cross Validation for Non-differentiable Penalties under High-dimensional Settings
di: Zou, Haolin, et al.
Pubblicazione: (2024)

Estimation of sparse linear regression coefficients under $L$-subexponential covariates
di: Sasai, Takeyuki
Pubblicazione: (2023)

Heavy-tailed and Horseshoe priors for regression and sparse Besov rates
di: Agapiou, Sergios, et al.
Pubblicazione: (2025)

On high-dimensional classification by sparse generalized Bayesian logistic regression
di: Mai, The Tien
Pubblicazione: (2024)

Contraction rates for sparse variational approximations in Gaussian process regression
di: Nieman, Dennis, et al.
Pubblicazione: (2021)

Adaptive posterior concentration rates for sparse high-dimensional linear regression with random design and unknown error variance
di: Mai, The Tien
Pubblicazione: (2024)

Asymptotic properties of adaptive group Lasso for sparse reduced rank regression
di: He, Kejun, et al.
Pubblicazione: (2016)

Testing for sparse idiosyncratic components in factor-augmented regression models
di: Beyhum, Jad, et al.
Pubblicazione: (2023)

Adaptive sparse variational approximations for Gaussian process regression
di: Nieman, Dennis, et al.
Pubblicazione: (2025)

Minimax Optimal rates of convergence in the shuffled regression, unlinked regression, and deconvolution under vanishing noise
di: Durot, Cecile, et al.
Pubblicazione: (2024)

On estimation of skewed stable linear regression
di: Kawamo, Eitaro, et al.
Pubblicazione: (2024)

Shape-restricted transfer learning analysis for generalized linear regression model
di: Li, Pengfei, et al.
Pubblicazione: (2024)

Theoretical limits of descending $\ell_0$ sparse-regression ML algorithms
di: Stojnic, Mihailo
Pubblicazione: (2024)

Nearly minimax empirical Bayesian prediction of independent Poisson observables
di: Li, Xiao
Pubblicazione: (2023)

Finite sample rates for logistic regression with small noise or few samples
di: Kuchelmeister, Felix, et al.
Pubblicazione: (2023)

Adaptive minimax estimation for discretely observed Lévy processes
di: Duval, Céline, et al.
Pubblicazione: (2024)

Robust linear regression under latent group heterogeneity
di: Li, Xifeng, et al.
Pubblicazione: (2026)

Nonparametric hazard rate estimation with associated kernels and minimax bandwidth choice
di: Breuil, Luce, et al.
Pubblicazione: (2025)

Valid F-screening in linear regression
di: McGough, Olivia, et al.
Pubblicazione: (2025)

On the Low-Temperature MCMC threshold: the cases of sparse tensor PCA, sparse regression, and a geometric rule
di: Chen, Zongchen, et al.
Pubblicazione: (2024)

Constructive and consistent estimation of quadratic minimax
di: Kennerberg, Philip, et al.
Pubblicazione: (2024)

Gaussian quasi-likelihood analysis for non-Gaussian linear mixed-effects model with system noise
di: Imamura, Takumi, et al.
Pubblicazione: (2024)

Asymptotic confidence interval for R2 in multiple linear regression
di: Dedecker, J, et al.
Pubblicazione: (2024)

Universality in block dependent linear models with applications to nonparametric regression
di: Lahiry, Samriddha, et al.
Pubblicazione: (2023)

No need for an oracle: the nonparametric maximum likelihood decision in the compound decision problem is minimax
di: Ritov, Ya'acov
Pubblicazione: (2023)

Posterior contraction rates in a sparse non-linear mixed-effects model
di: Naveau, Marion, et al.
Pubblicazione: (2024)

Linear regression with known noise distribution up to a scale: The reward of not using the OLSE
di: Balabdaoui, Fadoua, et al.
Pubblicazione: (2025)