Annals of Statistics

Article	Citations
Estimation and inference for minimizer and minimum of convex functions: Optimality, adaptivity and uncertainty principles	171
Inference in Ising models on dense regular graphs	111
Debiased regression adjustment in completely randomized experiments with moderately high-dimensional covariates	50
Deep horseshoe Gaussian processes	45
Parametric copula adjusted for non- and semiparametric regression	39
Half-trek criterion for identifiability of latent variable models	38
High-dimensional statistical inference for linkage disequilibrium score regression and its cross-ancestry extensions	35
Universal rank inference via residual subsampling with application to large networks	35
Efficiency in local differential privacy	33
A sieve stochastic gradient descent estimator for online nonparametric regression in Sobolev ellipsoids	32
Near-optimal inference in adaptive linear regression	31
Scalable estimation and inference for censored quantile regression process	31
On high-dimensional Poisson models with measurement error: Hypothesis testing for nonlinear nonconvex optimization	27
Deep learning for the partially linear Cox model	26
A geometrical analysis of kernel ridge regression and its applications	25
Spectral gap bounds for reversible hybrid Gibbs chains	25
A general characterization of optimal tie-breaker designs	24
Learning sparse graphons and the generalized Kesten–Stigum threshold	24
Inference for low-rank models	23
Consistent inference for diffusions from low frequency measurements	23
Uniform convergence of local Fréchet regression with applications to locating extrema and time warping for metric space valued trajectories	23
Asymptotic analysis of synchrosqueezing transform—toward statistical inference with nonlinear-type time-frequency analysis	23
Inference for low-rank tensors—no need to debias	22
Adaptive and robust multi-task learning	21
Yurinskii’s coupling for martingales	21

Admissible ways of merging p-values under arbitrary dependence	21
Sharp optimality for high-dimensional covariance testing under sparse signals	20
Fundamental limits of community detection from multi-view data: Multi-layer, dynamic and partially labeled block models	20
Fixed and random covariance regression analyses	20
Consistent order selection for ARFIMA processes	19
Limiting distributions for eigenvalues of sample correlation matrices from heavy-tailed populations	19
Environment invariant linear least squares	18
Spectral estimation of Hawkes processes from count data	18
On posterior consistency of data assimilation with Gaussian process priors: The 2D-Navier–Stokes equations	18
A common-cause principle for eliminating selection bias in causal estimands through covariate adjustment	18
Nonparametric classification with missing data	17
Change-point inference in high-dimensional regression models under temporal dependence	17
Is infinity that far? A Bayesian nonparametric perspective of finite mixture models	17
Refined Cramér-type moderate deviation theorems for general self-normalized sums with applications to dependent random variables and winsorized mean	17
Rank and factor loadings estimation in time series tensor factor model by pre-averaging	17
Testing goodness-of-fit and conditional independence with approximate co-sufficient sampling	16
Order-of-addition orthogonal arrays to study the effect of treatment ordering	16
Rate-optimal estimation of mixed semimartingales	16
Supervised homogeneity fusion: A combinatorial approach	16
New Edgeworth-type expansions with finite sample guarantees	16
Asymptotic distribution of maximum likelihood estimator in generalized linear mixed models with crossed random effects	15
A nonparametric test for elliptical distribution based on kernel embedding of probabilities	15
On the multiway principal component analysis	15
Iterative algorithm for discrete structure recovery	15
On the convergence of coordinate ascent variational inference	15
Distributed nonparametric function estimation: Optimal rate of convergence and cost of adaptation	15
Plugin estimation of smooth optimal transport maps	15
Spatial dependence and space–time trend in extreme events	15
The numeraire e-variable and reverse information projection	14
General spatio-temporal factor models for high-dimensional random fields on a lattice	14
Consistency of Bayesian inference for multivariate max-stable distributions	14
The Lasso with general Gaussian designs with applications to hypothesis testing	14
Toward theoretical understandings of robust Markov decision processes: Sample complexity and asymptotics	14
Minimax rate for multivariate data under componentwise local differential privacy constraints	14
Time-uniform central limit theory and asymptotic confidence sequences	13
Learning mixtures of permutations: Groups of pairwise comparisons and combinatorial method of moments	13
Sup-norm adaptive drift estimation for multivariate nonreversible diffusions	13
Transfer learning for contextual multi-armed bandits	12
Edgeworth expansions for network moments	12
Algorithmic stability implies training-conditional coverage for distribution-free prediction methods	12
Consistency of invariance-based randomization tests	12
Wald tests when restrictions are locally singular	12
Computational lower bounds for graphon estimation via low-degree polynomials	12
Backfitting for large scale crossed random effects regressions	12
A new approach to tests and confidence bands for distribution functions	11
Minimax nonparametric estimation of pure quantum states	11
Sharp adaptive and pathwise stable similarity testing for scalar ergodic diffusions	11
Dimension free ridge regression	11
Change acceleration and detection	11
Minimax rate of distribution estimation on unknown submanifolds under adversarial losses	11

Testing nonparametric shape restrictions	11
Surprises in high-dimensional ridgeless least squares interpolation	11
Interactive versus noninteractive locally differentially private estimation: Two elbows for the quadratic functional	11
Projected state-action balancing weights for offline reinforcement learning	11
Linear biomarker combination for constrained classification	11
Finite-sample complexity of sequential Monte Carlo estimators	11
Testing community structure for hypergraphs	10
ARK: Robust knockoffs inference with coupling	10
Dispersal density estimation across scales	10
Approximate Message Passing algorithms for rotationally invariant matrices	10
Testing for independence in high dimensions based on empirical copulas	10
The Stein effect for Fréchet means	10
Nonlinear global Fréchet regression for random objects via weak conditional expectation	10
Noisy linear inverse problems under convex constraints: Exact risk asymptotics in high dimensions	10
Detecting multiple replicating signals using adaptive filtering procedures	10
Bridging factor and sparse models	10
Ridge regression revisited: Debiasing, thresholding and bootstrap	10
Confidence regions near singular information and boundary points with applications to mixed models	10
On least squares estimation under heteroscedastic and heavy-tailed errors	10
On universally consistent and fully distribution-free rank tests of vector independence	9
ℓ2 inference for change points in high-dimensional time series via a Two-Way MOSUM	9
Testing high-dimensional regression coefficients in linear models	9
Tensor clustering with planted structures: Statistical optimality and computational limits	9
On the sample complexity of entropic optimal transport	9
Carving model-free inference	9
Semiparametric inference based on adaptively collected data	9
Adaptive estimation in multivariate response regression with hidden variables	9
A flexible defense against the winner’s curse	9
Correction note: “Asymptotic spectral theory for nonlinear time series”	9
Entrywise dynamics and universality of general first order methods	8
Large-dimensional independent component analysis: Statistical optimality and computational tractability	8
Statistical inference for principal components of spiked covariance matrices	8
Online estimation with rolling validation: Adaptive nonparametric estimation with streaming data	8
Joint sequential detection and isolation for dependent data streams	8
Conformal inference for random objects	8
A nonparametric doubly robust test for a continuous treatment effect	8
Local convexity of the TAP free energy and AMP convergence for Z2-synchronization	8
Asymptotic distributions of largest Pearson correlation coefficients under dependent structures	8
Matching recovery threshold for correlated random graphs	8
Ensemble projection pursuit for general nonparametric regression	8
Local permutation tests for conditional independence	7
Multivariate trend filtering for lattice data	7
Bootstrapping persistent Betti numbers and other stabilizing statistics	7
The online closure principle	7
A general framework to quantify deviations from structural assumptions in the analysis of nonstationary function-valued processes	7
Adaptive variational Bayes: Optimality, computation and applications	7
Affine-equivariant inference for multivariate location under Lp loss functions	7
Efficient estimation of the maximal association between multiple predictors and a survival outcome	7
Heavy-tailed Bayesian nonparametric adaptation	7
Embedding distributional data	7
Sparse high-dimensional linear regression. Estimating squared error and a phase transition	7
Spectral analysis of gram matrices with missing at random observations: Convergence, central limit theorems, and applications in statistical inference	7
Symmetry: A general structure in nonparametric regression	7
Rerandomization with diminishing covariate imbalance and diverging number of covariates	6
A two-way heterogeneity model for dynamic networks	6
Adaptive novelty detection with false discovery rate guarantee	6
Kurtosis-based projection pursuit for matrix-valued data	6
Some theory about efficient dimension reduction regarding the interaction between two responses	6
On robustness and local differential privacy	6
Optimal signal detection in some spiked random matrix models: Likelihood ratio tests and linear spectral statistics	6
Rates of estimation for high-dimensional multireference alignment	6
General and feasible tests with multiply-imputed datasets	6
Post-selection inference via algorithmic stability	6
Global and individualized community detection in inhomogeneous multilayer networks	6
Self-normalized Cramér type moderate deviation theorem for Gaussian approximation	6
Total positivity in multivariate extremes	6
Estimating a density near an unknown manifold: A Bayesian nonparametric approach	6
Convergence of de Finetti’s mixing measure in latent structure models for observed exchangeable sequences	5
Estimation of the spectral measure from convex combinations of regularly varying random vectors	5
Asymptotically-exact selective inference for quantile regression	5
Distributed adaptive Gaussian mean estimation with unknown variance: Interactive protocol helps adaptation	5
Structured matrix learning under arbitrary entrywise dependence and estimation of Markov transition kernel	5
Convex regression in multidimensions: Suboptimality of least squares estimators	5
Universal regression with adversarial responses	5
Optimal false discovery rate control for large scale multiple testing with auxiliary information	5
On minimax optimality of sparse Bayes predictive density estimates	5
Gaussian process regression in the flat limit	5
A statistical framework of watermarks for large language models: Pivot, detection efficiency and optimal rules	5
Rate-optimal robust estimation of high-dimensional vector autoregressive models	5
A study of orthogonal array-based designs under a broad class of space-filling criteria	5

A unified analysis of likelihood-based estimators in the Plackett–Luce model	5
Conditional calibration for false discovery rate control under dependence	5
A new and flexible design construction for orthogonal arrays for modern applications	5
Bootstrap-assisted inference for generalized Grenander-type estimators	5
Approximation error from discretizations and its applications	5
On the existence of powerful p-values and e-values for composite hypotheses	5
Grouped variable selection with discrete optimization: Computational and statistical perspectives	5
A conformal test of linear models via permutation-augmented regressions	5
False discovery rate control with unknown null distribution: Is it possible to mimic the oracle?	5
Model selection in the space of Gaussian models invariant by symmetry	5
Statistical complexity and optimal algorithms for nonlinear ridge bandits	5
Improved covariance estimation: Optimal robustness and sub-Gaussian guarantees under heavy tails	5
Skewed Bernstein–von Mises theorem and skew-modal approximations	5
Deep neural networks for nonparametric interaction models with diverging dimension	5
Central limit theorem and bootstrap approximation in high dimensions: Near 1/n rates via implicit smoothing	5
S-estimation in linear models with structured covariance matrices	5
Stereographic Markov chain Monte Carlo	5
Optimal subgroup selection	5
Conditional predictive inference for stable algorithms	5
Extreme value inference for heterogeneous power law data	5
MARS via LASSO	5
Higher criticism to compare two large frequency tables, with sensitivity to possible rare and weak differences	4
Early stopping for L2-boosting in high-dimensional linear models	4
Non-independent component analysis	4
The edge of discovery: Controlling the local false discovery rate at the margin	4
Fundamental limits of low-rank matrix estimation with diverging aspect ratios	4
Uniform consistency in nonparametric mixture models	4
Optimal policy evaluation using kernel-based temporal difference methods	4
Optimal difference-based variance estimators in time series: A general framework	4
Deep approximate policy iteration	4
How do noise tails impact on deep ReLU networks?	4
Semi-supervised U-statistics	4
One-step estimation of differentiable Hilbert-valued parameters	4
Precise error rates for computationally efficient testing	4
Isotonic regression with unknown permutations: Statistics, computation and adaptation	4
Stochastic continuum-armed bandits with additive models: Minimax regrets and adaptive algorithm	4
StarTrek: Combinatorial variable selection with false discovery rate control	4
Random graph asymptotics for treatment effect estimation under network interference	4
Quantile processes and their applications in finite populations	4
The generalization error of max-margin linear classifiers: Benign overfitting and high dimensional asymptotics in the overparametrized regime	4
High-dimensional inference for dynamic treatment effects	4
Theory of functional principal component analysis for discretely observed data	4
The curse of overparametrization in adversarial training: Precise analysis of robust generalization for random features regression	4
Concentration of discrepancy-based approximate Bayesian computation via Rademacher complexity	4
Tests of missing completely at random based on sample covariance matrices	4
On the statistical complexity of sample amplification	4
Dimension-free mixing times of Gibbs samplers for Bayesian hierarchical models	4
Spectral statistics of sample block correlation matrices	4
Learning low-dimensional nonlinear structures from high-dimensional noisy data: An integral operator approach	4
Counterfactual inference in sequential experiments	3
Optimal heteroskedasticity testing in nonparametric regression	3
Increasing dimension asymptotics for two-way crossed mixed effect models	3
Sharp global convergence guarantees for iterative nonconvex optimization with random data	3
Parameter estimation in nonlinear multivariate stochastic differential equations based on splitting schemes	3
Robust transfer learning with unreliable source data	3
Higher-order entrywise eigenvectors analysis of low-rank random matrices: Bias correction, Edgeworth expansion and bootstrap	3
Low-degree hardness of detection for correlated Erdős–Rényi graphs	3
Generalization error bounds of dynamic treatment regimes in penalized regression-based learning	3
Inference for extremal regression with dependent heavy-tailed data	3
Complexity analysis of Bayesian learning of high-dimensional DAG models and their equivalence classes	3
Covariance estimation under one-bit quantization	3
Sparse anomaly detection across referentials: A rank-based higher criticism approach	3
Testing equivalence of clustering	3
Asymptotic normality and optimality in nonsmooth stochastic approximation	3
Exact minimax risk for linear least squares, and the lower tail of sample covariance matrices	3
Approximate kernel PCA: Computational versus statistical trade-off	3
Empirical partially Bayes multiple testing and compound χ2 decisions	3
AutoRegressive approximations to nonstationary time series with inference and applications	3
Metric statistics: Exploration and inference for random objects with distance profiles	3
Higher-order coverage errors of batching methods via Edgeworth expansions on t-statistics	3
A cross-validation framework for signal denoising with applications to trend filtering, dyadic CART and beyond	3
Tensor factor model estimation by iterative projection	3
Optimization hierarchy for fair statistical decision problems	3
On blockwise and reference panel-based estimators for genetic data prediction in high dimensions	3
Functional sufficient dimension reduction through average Fréchet derivatives	3
Robust sub-Gaussian estimation of a mean vector in nearly linear time	3
Statistical-computational trade-offs in tensor PCA and related problems via communication complexity	3
Projective, sparse and learnable latent position network models	3
Testing for practically significant dependencies in high dimensions via bootstrapping maxima of U-statistics	3
Simplex quantile regression without crossing	3
Evidence factors from multiple, possibly invalid, instrumental variables	3
Reinforcement learning for individual optimal policy from heterogeneous data	3
High-dimensional Hilbert–Schmidt linear regression with Hilbert manifold variables	3
Causality pursuit from heterogeneous environments via neural adversarial invariance learning	3
High-dimensional asymptotics of likelihood ratio tests in the Gaussian sequence model under convex constraints	3
Online change-point detection for matrix-valued time series with latent two-way factor structure	3
Powerful knockoffs via minimizing reconstructability	3
Choosing between persistent and stationary volatility	3
Unified algorithms for RL with Decision-Estimation Coefficients: PAC, reward-free, preference-based learning and beyond	3
Dimension reduction for functional data based on weak conditional moments	3
On an extension of the promotion time cure model	3
Variable selection, monotone likelihood ratio and group sparsity	3
Gromov–Wasserstein distances: Entropic regularization, duality and sample complexity	3