Cover Image

Optimality and computational barriers in variable selection under dependence

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gao, Ming, Aragam, Bryon
Format:	Preprint
Published:	2025
Subjects:	Statistics Theory
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

KL-BSS: Rethinking optimality for neighbourhood selection in structural equation models
by: Gao, Ming, et al.
Published: (2023)

Optimal structure learning and conditional independence testing
by: Gao, Ming, et al.
Published: (2025)

Greedy equivalence search for nonparametric graphical models
by: Aragam, Bryon
Published: (2024)

Differentiable Structure Learning and Causal Discovery for General Binary Data
by: Deng, Chang, et al.
Published: (2025)

Model-free Estimation of Latent Structure via Multiscale Nonparametric Maximum Likelihood
by: Aragam, Bryon, et al.
Published: (2024)

Beyond identifiability: Learning causal representations with few environments and finite samples
by: Lee, Inbeom, et al.
Published: (2026)

Learning general conditional independence structures via the neighbourhood lattice
by: Amini, Arash A., et al.
Published: (2022)

Markov Equivalence and Consistency in Differentiable Structure Learning
by: Deng, Chang, et al.
Published: (2024)

Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models
by: Rajendran, Goutham, et al.
Published: (2024)

An instrumental variable approach under dependent censoring
by: Crommen, Gilles, et al.
Published: (2022)

Breaking the curse of dimensionality in structured density estimation
by: Vandermeulen, Robert A., et al.
Published: (2024)

Dimension-independent rates for structured neural density estimation
by: Vandermeulen, Robert A., et al.
Published: (2024)

Computational barriers for permutation-based problems, and cumulants of weakly dependent random variables
by: Even, Bertrand, et al.
Published: (2025)

Thresholded Lasso for high dimensional variable selection
by: Zhou, Shuheng
Published: (2023)

Sharp bounds for products of dependent random variables
by: Blier-Wong, Christopher, et al.
Published: (2026)

Estimation and variable selection in high dimension in nonlinear mixed-effects models
by: Caillebotte, Antoine, et al.
Published: (2025)

Robust variable selection for partially linear additive models
by: Boente, Graciela, et al.
Published: (2024)

Stochastic dominance of sums of risks under dependence conditions
by: Navarro, Jorge, et al.
Published: (2025)

Quantile regression under dependent censoring with unknown association
by: D'Haen, Myrthe, et al.
Published: (2024)

Topological reconstruction of compact supports of dependent stationary random variables
by: Kallel, Sadok, et al.
Published: (2023)

Adaptive variational Bayes: Optimality, computation and applications
by: Ohn, Ilsang, et al.
Published: (2021)

Causal inference under interference: computational barriers and algorithmic solutions
by: Bhattacharya, Sohom, et al.
Published: (2025)

On sums of dependent random lifetimes under the Time Transformed Exponential model
by: Navarro, Jorge, et al.
Published: (2024)

Usual stochastic orderings of the second-order statistics with dependent heterogeneous semi-parametric distribution random variables
by: Lv, Guoqiang
Published: (2024)

Non-parametric estimation of net survival under dependence between death causes
by: Laverny, Oskar, et al.
Published: (2025)

Multiple testing under negative dependence
by: Chi, Ziyu, et al.
Published: (2022)

Estimation and variable selection in high dimension in a causal joint model of survival times and longitudinal outcomes with random effects
by: Caillebotte, Antoine, et al.
Published: (2023)

Nonequilibrium statistics of barrier crossings with competing pathways
by: Ahmad, Gulzar, et al.
Published: (2025)

Fast localization of anomalous patches in spatial data under dependence
by: Bonnerjee, Soham, et al.
Published: (2026)

U-statistics of local sample moments under weak dependence
by: Dehling, Herold G., et al.
Published: (2023)

Multivariate Priors and the Linearity of Optimal Bayesian Estimators under Gaussian Noise
by: Barnes, Leighton P., et al.
Published: (2024)

Optimal e-values for testing the mean of a bounded random variable against a composite alternative
by: Arnold, Sebastian, et al.
Published: (2026)

Distinguishability of causal structures under latent confounding and selection
by: Carey, Ryan, et al.
Published: (2025)

Optimal estimation of Gaussian (poly)trees
by: Wang, Yuhao, et al.
Published: (2024)

Optimal Decision Rules for Composite Binary Hypothesis Testing under Neyman-Pearson Framework
by: Song, Yanglei, et al.
Published: (2025)

Stable Phase Retrieval: Optimal Rates in Poisson and Heavy-tailed Models
by: Huang, Gao, et al.
Published: (2025)

Optimal Design under Interference, Homophily, and Robustness Trade-offs
by: Thiyageswaran, Vydhourie, et al.
Published: (2026)

Correlation bounds, mixing and m-dependence under random time-varying network distances with an application to Cox-Processes
by: Kreiss, Alexander
Published: (2019)

The noise barrier and the large signal bias of the Lasso and other convex estimators
by: Bellec, Pierre C
Published: (2018)

Optimal estimation of the null distribution in large-scale inference
by: Kotekal, Subhodh, et al.
Published: (2024)