Annals of Statistics

Article	Citations
Estimation and inference for minimizer and minimum of convex functions: Optimality, adaptivity and uncertainty principles	158
Debiased regression adjustment in completely randomized experiments with moderately high-dimensional covariates	59
High-dimensional statistical inference for linkage disequilibrium score regression and its cross-ancestry extensions	56
On high-dimensional Poisson models with measurement error: Hypothesis testing for nonlinear nonconvex optimization	47
Inference in Ising models on dense regular graphs	44
Deep horseshoe Gaussian processes	40
Efficiency in local differential privacy	36
Near-optimal inference in adaptive linear regression	35
Universal rank inference via residual subsampling with application to large networks	34
Optimal convex M-estimation via score matching	29
A sieve stochastic gradient descent estimator for online nonparametric regression in Sobolev ellipsoids	28
Scalable estimation and inference for censored quantile regression process	28
Half-trek criterion for identifiability of latent variable models	27
A geometrical analysis of kernel ridge regression and its applications	27
Fundamental limits of community detection from multi-view data: Multi-layer, dynamic and partially labeled block models	26
Deep learning for the partially linear Cox model	26
Learning sparse graphons and the generalized Kesten–Stigum threshold	25
A general characterization of optimal tie-breaker designs	24
Inference for low-rank models	23
Trace test for high-dimensional cointegration	22
Consistent inference for diffusions from low frequency measurements	22
Rank tests for PCA under weak identifiability	22
Spectrum-aware debiasing: A modern inference framework with applications to principal components regression	21
Adaptive and robust multi-task learning	21
Yurinskii’s coupling for martingales	20

Sharp optimality for high-dimensional covariance testing under sparse signals	19
Asymptotic analysis of synchrosqueezing transform—toward statistical inference with nonlinear-type time-frequency analysis	19
Uniform convergence of local Fréchet regression with applications to locating extrema and time warping for metric space valued trajectories	19
Spectral gap bounds for reversible hybrid Gibbs chains	19
Order-of-addition orthogonal arrays to study the effect of treatment ordering	18
On posterior consistency of data assimilation with Gaussian process priors: The 2D-Navier–Stokes equations	18
Spectral estimation of Hawkes processes from count data	18
Limiting distributions for eigenvalues of sample correlation matrices from heavy-tailed populations	18
Testing goodness-of-fit and conditional independence with approximate co-sufficient sampling	17
Fixed and random covariance regression analyses	17
Near optimal sample complexity for matrix and tensor normal models via geodesic convexity	17
Environment invariant linear least squares	17
Nonparametric classification with missing data	16
Rate-optimal estimation of mixed semimartingales	16
A common-cause principle for eliminating selection bias in causal estimands through covariate adjustment	16
Consistent order selection for ARFIMA processes	16
Supervised homogeneity fusion: A combinatorial approach	16
Rank and factor loadings estimation in time series tensor factor model by pre-averaging	16
Change-point inference in high-dimensional regression models under temporal dependence	16
Is infinity that far? A Bayesian nonparametric perspective of finite mixture models	16
A nonparametric test for elliptical distribution based on kernel embedding of probabilities	15
New Edgeworth-type expansions with finite sample guarantees	15
Object detection under the linear subspace model with application to cryo-EM images	15
General spatio-temporal factor models for high-dimensional random fields on a lattice	15
Consistency of invariance-based randomization tests	14
Asymptotic distribution of maximum likelihood estimator in generalized linear mixed models with crossed random effects	14
Toward theoretical understandings of robust Markov decision processes: Sample complexity and asymptotics	14
Plugin estimation of smooth optimal transport maps	14
Consistency of Bayesian inference for multivariate max-stable distributions	14
On the convergence of coordinate ascent variational inference	14
The numeraire e-variable and reverse information projection	14
On the structural dimension of sliced inverse regression	14
On the multiway principal component analysis	14
Algorithmic stability implies training-conditional coverage for distribution-free prediction methods	13
Computational lower bounds for graphon estimation via low-degree polynomials	13
The Lasso with general Gaussian designs with applications to hypothesis testing	13
Learning mixtures of permutations: Groups of pairwise comparisons and combinatorial method of moments	13
Projected state-action balancing weights for offline reinforcement learning	13
Time-uniform central limit theory and asymptotic confidence sequences	13
Testing nonparametric shape restrictions	13
Sup-norm adaptive drift estimation for multivariate nonreversible diffusions	13
Minimax rate for multivariate data under componentwise local differential privacy constraints	13
Transfer learning for contextual multi-armed bandits	13
Minimax rate of distribution estimation on unknown submanifolds under adversarial losses	13
Communication-efficient and distributed-oracle estimation for high-dimensional quantile regression	13
Wald tests when restrictions are locally singular	13
Interactive versus noninteractive locally differentially private estimation: Two elbows for the quadratic functional	12
Sharp adaptive and pathwise stable similarity testing for scalar ergodic diffusions	12
Finite-sample complexity of sequential Monte Carlo estimators	12
Linear biomarker combination for constrained classification	12

Testing for independence in high dimensions based on empirical copulas	12
Change acceleration and detection	12
Confounder selection via iterative graph expansion	11
A new approach to tests and confidence bands for distribution functions	11
Confidence regions near singular information and boundary points with applications to mixed models	11
Noisy linear inverse problems under convex constraints: Exact risk asymptotics in high dimensions	11
Carving model-free inference	10
Dispersal density estimation across scales	10
ARK: Robust knockoffs inference with coupling	10
A flexible defense against the winner’s curse	10
Dimension free ridge regression	10
The distributionally robust prediction error of the LASSO and related estimators	10
The Stein effect for Fréchet means	10
Detecting multiple replicating signals using adaptive filtering procedures	10
On the sample complexity of entropic optimal transport	10
On universally consistent and fully distribution-free rank tests of vector independence	9
Correction note: “Asymptotic spectral theory for nonlinear time series”	9
Nonlinear global Fréchet regression for random objects via weak conditional expectation	9
Ridge regression revisited: Debiasing, thresholding and bootstrap	9
Bridging factor and sparse models	9
ℓ2 inference for change points in high-dimensional time series via a Two-Way MOSUM	9
Online estimation with rolling validation: Adaptive nonparametric estimation with streaming data	8
Asymptotic distributions of largest Pearson correlation coefficients under dependent structures	8
Local convexity of the TAP free energy and AMP convergence for Z2-synchronization	8
Conformal inference for random objects	8
Semiparametric inference based on adaptively collected data	8
Information theoretic limits of robust sub-Gaussian mean estimation under star-shaped constraints	8
Matching recovery threshold for correlated random graphs	8
Dualizing Le Cam’s method for functional estimation I: General theory	8
Large-dimensional independent component analysis: Statistical optimality and computational tractability	8
Entrywise dynamics and universality of general first order methods	8
Joint sequential detection and isolation for dependent data streams	8
Testing high-dimensional regression coefficients in linear models	8
Post-selection inference via algorithmic stability	7
Local permutation tests for conditional independence	7
Embedding distributional data	7
Some theory about efficient dimension reduction regarding the interaction between two responses	7
Ensemble projection pursuit for general nonparametric regression	7
Bootstrapping persistent Betti numbers and other stabilizing statistics	7
Efficient estimation of the maximal association between multiple predictors and a survival outcome	7
Spectral analysis of gram matrices with missing at random observations: Convergence, central limit theorems, and applications in statistical inference	7
Adaptive variational Bayes: Optimality, computation and applications	7
Global and individualized community detection in inhomogeneous multilayer networks	7
A nonparametric doubly robust test for a continuous treatment effect	7
On robustness and local differential privacy	7
Symmetry: A general structure in nonparametric regression	7
Multivariate trend filtering for lattice data	7
Rerandomization with diminishing covariate imbalance and diverging number of covariates	7
A two-way heterogeneity model for dynamic networks	7
A general framework to quantify deviations from structural assumptions in the analysis of nonstationary function-valued processes	7
Self-normalized Cramér type moderate deviation theorem for Gaussian approximation	7
The online closure principle	7
Affine-equivariant inference for multivariate location under Lp loss functions	7
Heavy-tailed Bayesian nonparametric adaptation	7
Conditional calibration for false discovery rate control under dependence	6
Rates of estimation for high-dimensional multireference alignment	6
Optimal signal detection in some spiked random matrix models: Likelihood ratio tests and linear spectral statistics	6
Asymptotically-exact selective inference for quantile regression	6
Deep neural networks for nonparametric interaction models with diverging dimension	6
Universal regression with adversarial responses	6
Kurtosis-based projection pursuit for matrix-valued data	6
Adaptive novelty detection with false discovery rate guarantee	6
Central limit theorem and bootstrap approximation in high dimensions: Near 1/n rates via implicit smoothing	6
Convex regression in multidimensions: Suboptimality of least squares estimators	6
Structured matrix learning under arbitrary entrywise dependence and estimation of Markov transition kernel	6
Estimating a density near an unknown manifold: A Bayesian nonparametric approach	6
Total positivity in multivariate extremes	6
Approximation error from discretizations and its applications	6
Stereographic Markov chain Monte Carlo	6
S-estimation in linear models with structured covariance matrices	6
Distributed adaptive Gaussian mean estimation with unknown variance: Interactive protocol helps adaptation	5
Gaussian process regression in the flat limit	5
Skewed Bernstein–von Mises theorem and skew-modal approximations	5
Optimal subgroup selection	5
Grouped variable selection with discrete optimization: Computational and statistical perspectives	5
A study of orthogonal array-based designs under a broad class of space-filling criteria	5
One-step estimation of differentiable Hilbert-valued parameters	5
The curse of overparametrization in adversarial training: Precise analysis of robust generalization for random features regression	5
Statistical complexity and optimal algorithms for nonlinear ridge bandits	5
Semiparametric Bernstein–von Mises phenomenon via Isotonized Posterior in Wicksell’s problem	5

Bootstrap-assisted inference for generalized Grenander-type estimators	5
Improved covariance estimation: Optimal robustness and sub-Gaussian guarantees under heavy tails	5
A new and flexible design construction for orthogonal arrays for modern applications	5
Model selection in the space of Gaussian models invariant by symmetry	5
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
Rate-optimal robust estimation of high-dimensional vector autoregressive models	5
Conditional predictive inference for stable algorithms	5
On the existence of powerful p-values and e-values for composite hypotheses	5
Scalable inference in functional linear regression with streaming data	5
A unified analysis of likelihood-based estimators in the Plackett–Luce model	5
Semi-supervised U-statistics	5
Generalized multilinear models for sufficient dimension reduction on tensor-valued predictors	4
Finite- and large sample inference for model and coefficients in high-dimensional linear regression with repro samples	4
Projective, sparse and learnable latent position network models	4
Fundamental limits of low-rank matrix estimation with diverging aspect ratios	4
Exact minimax risk for linear least squares, and the lower tail of sample covariance matrices	4
StarTrek: Combinatorial variable selection with false discovery rate control	4
Dimension-free mixing times of Gibbs samplers for Bayesian hierarchical models	4
Tests of missing completely at random based on sample covariance matrices	4
Non-independent component analysis	4
Random graph asymptotics for treatment effect estimation under network interference	4
How do noise tails impact on deep ReLU networks?	4
Early stopping for L2-boosting in high-dimensional linear models	4
Extreme value inference for heterogeneous power law data	4
A conformal test of linear models via permutation-augmented regressions	4
The edge of discovery: Controlling the local false discovery rate at the margin	4
Optimal policy evaluation using kernel-based temporal difference methods	4
Asymptotic normality and optimality in nonsmooth stochastic approximation	4
Gromov–Wasserstein distances: Entropic regularization, duality and sample complexity	4
On the statistical complexity of sample amplification	4
Statistical-computational trade-offs in tensor PCA and related problems via communication complexity	4
Optimal difference-based variance estimators in time series: A general framework	4
The generalization error of max-margin linear classifiers: Benign overfitting and high dimensional asymptotics in the overparametrized regime	4
Deep approximate policy iteration	4
Theory of functional principal component analysis for discretely observed data	4
Higher criticism to compare two large frequency tables, with sensitivity to possible rare and weak differences	4
A statistical framework of watermarks for large language models: Pivot, detection efficiency and optimal rules	4
Spectral statistics of sample block correlation matrices	4
Learning low-dimensional nonlinear structures from high-dimensional noisy data: An integral operator approach	4
Sparse anomaly detection across referentials: A rank-based higher criticism approach	4
Counterfactual inference in sequential experiments	4
Quantile processes and their applications in finite populations	4
Stochastic continuum-armed bandits with additive models: Minimax regrets and adaptive algorithm	4
Uniform consistency in nonparametric mixture models	4
Testing for practically significant dependencies in high dimensions via bootstrapping maxima of U-statistics	4
Concentration of discrepancy-based approximate Bayesian computation via Rademacher complexity	4
High-dimensional inference for dynamic treatment effects	4
Precise asymptotics of bagging regularized M-estimators	4
Precise error rates for computationally efficient testing	4
MARS via LASSO	4
Precise statistical analysis of classification accuracies for adversarial training	3
Complexity analysis of Bayesian learning of high-dimensional DAG models and their equivalence classes	3
A statistical framework for analyzing shape in a time series of random geometric objects	3
Average partial effect estimation using double machine learning	3
Settling the sample complexity of model-based offline reinforcement learning	3
Optimality of approximate message passing for spiked matrix models with rotationally invariant noise	3
Optimization hierarchy for fair statistical decision problems	3
Inference for extremal regression with dependent heavy-tailed data	3
Versatile differentially private learning for general loss functions	3
Multivariate root-n-consistent smoothing parameter-free matching estimators and estimators of inverse density weighted expectations	3
Robust transfer learning with unreliable source data	3
Higher-order coverage errors of batching methods via Edgeworth expansions on t-statistics	3
Empirical partially Bayes multiple testing and compound χ2 decisions	3
The impacts of unobserved covariates on covariate-adaptive randomized experiments	3
Graphical models for nonstationary time series	3
Semiparametric modeling and analysis for longitudinal network data	3
Generalization error bounds of dynamic treatment regimes in penalized regression-based learning	3
Optimal estimation of high-dimensional Gaussian location mixtures	3
Simplex quantile regression without crossing	3
High-dimensional Hilbert–Schmidt linear regression with Hilbert manifold variables	3
Berry–Esseen bounds for design-based causal inference with possibly diverging treatment levels and varying group sizes	3
Reinforcement learning for individual optimal policy from heterogeneous data	3
Optimal heteroskedasticity testing in nonparametric regression	3
A cross-validation framework for signal denoising with applications to trend filtering, dyadic CART and beyond	3
Unified algorithms for RL with Decision-Estimation Coefficients: PAC, reward-free, preference-based learning and beyond	3
Variable selection, monotone likelihood ratio and group sparsity	3
Sharp global convergence guarantees for iterative nonconvex optimization with random data	3
Clustering by hill-climbing: Consistency results	3
Characterizing the SLOPE trade-off: A variational perspective and the Donoho–Tanner limit	3
Online estimation and inference for robust policy evaluation in reinforcement learning	3
Optimal nonparametric testing of Missing Completely At Random and its connections to compatibility	3
Higher-order entrywise eigenvectors analysis of low-rank random matrices: Bias correction, Edgeworth expansion and bootstrap	3
Metric statistics: Exploration and inference for random objects with distance profiles	3
Choosing between persistent and stationary volatility	3
Online change-point detection for matrix-valued time series with latent two-way factor structure	3
Low-degree hardness of detection for correlated Erdős–Rényi graphs	3
Distributionally robust learning for multisource unsupervised domain adaptation	3
On blockwise and reference panel-based estimators for genetic data prediction in high dimensions	3
Parameter estimation in nonlinear multivariate stochastic differential equations based on splitting schemes	3
Tensor factor model estimation by iterative projection	3
AutoRegressive approximations to nonstationary time series with inference and applications	3
Causality pursuit from heterogeneous environments via neural adversarial invariance learning	3
Conditional sequential Monte Carlo in high dimensions	3
Continuous-time targeted minimum loss-based estimation of intervention-specific mean outcomes	3