Annals of Statistics

Article	Citations
Estimation and inference for minimizer and minimum of convex functions: Optimality, adaptivity and uncertainty principles	206
High-dimensional statistical inference for linkage disequilibrium score regression and its cross-ancestry extensions	68
Inference in Ising models on dense regular graphs	53
Near-optimal inference in adaptive linear regression	50
A sieve stochastic gradient descent estimator for online nonparametric regression in Sobolev ellipsoids	43
Efficiency in local differential privacy	39
Half-trek criterion for identifiability of latent variable models	32
Deep horseshoe Gaussian processes	31
On high-dimensional Poisson models with measurement error: Hypothesis testing for nonlinear nonconvex optimization	31
Approximate independence of permutation mixtures	31
Scalable estimation and inference for censored quantile regression process	28
A geometrical analysis of kernel ridge regression and its applications	28
Optimal convex M-estimation via score matching	26
Universal rank inference via residual subsampling with application to large networks	26
Fundamental limits of community detection from multi-view data: Multi-layer, dynamic and partially labeled block models	25
Debiased regression adjustment in completely randomized experiments with moderately high-dimensional covariates	25
Learning sparse graphons and the generalized Kesten–Stigum threshold	24
A general characterization of optimal tie-breaker designs	23
Rank tests for PCA under weak identifiability	22
Trace test for high-dimensional cointegration	22
Consistent inference for diffusions from low frequency measurements	21
Asymptotic analysis of synchrosqueezing transform—toward statistical inference with nonlinear-type time-frequency analysis	20
Spectrum-aware debiasing: A modern inference framework with applications to principal components regression	20
Adaptive and robust multi-task learning	20
Spectral gap bounds for reversible hybrid Gibbs chains	19

Gradient descent inference in empirical risk minimization	18
Change-point inference in high-dimensional regression models under temporal dependence	18
Inference for low-rank models	18
Sharp optimality for high-dimensional covariance testing under sparse signals	18
Yurinskii’s coupling for martingales	18
On posterior consistency of data assimilation with Gaussian process priors: The 2D-Navier–Stokes equations	18
Statistical-computational trade-offs for recursive adaptive partitioning estimators	17
A common-cause principle for eliminating selection bias in causal estimands through covariate adjustment	17
Near optimal sample complexity for matrix and tensor normal models via geodesic convexity	17
Rank and factor loadings estimation in time series tensor factor model by pre-averaging	17
Fixed and random covariance regression analyses	17
Rate-optimal estimation of mixed semimartingales	17
Environment invariant linear least squares	17
Order-of-addition orthogonal arrays to study the effect of treatment ordering	16
Supervised homogeneity fusion: A combinatorial approach	16
Testing goodness-of-fit and conditional independence with approximate co-sufficient sampling	15
Is infinity that far? A Bayesian nonparametric perspective of finite mixture models	15
A nonparametric test for elliptical distribution based on kernel embedding of probabilities	15
Toward theoretical understandings of robust Markov decision processes: Sample complexity and asymptotics	15
Nonparametric classification with missing data	15
Limiting distributions for eigenvalues of sample correlation matrices from heavy-tailed populations	15
Object detection under the linear subspace model with application to cryo-EM images	15
New Edgeworth-type expansions with finite sample guarantees	15
General spatio-temporal factor models for high-dimensional random fields on a lattice	15
Asymptotic distribution of maximum likelihood estimator in generalized linear mixed models with crossed random effects	14
On the convergence of coordinate ascent variational inference	14
On the multiway principal component analysis	14
Learning extremal graphical structures in high dimensions	14
On the structural dimension of sliced inverse regression	14
Plugin estimation of smooth optimal transport maps	13
The numeraire e-variable and reverse information projection	13
Minimax rate for multivariate data under componentwise local differential privacy constraints	13
Consistency of invariance-based randomization tests	13
Projected state-action balancing weights for offline reinforcement learning	13
Transfer learning for contextual multi-armed bandits	13
Minimax rate of distribution estimation on unknown submanifolds under adversarial losses	13
Learning mixtures of permutations: Groups of pairwise comparisons and combinatorial method of moments	13
The Lasso with general Gaussian designs with applications to hypothesis testing	12
Wald tests when restrictions are locally singular	12
Time-uniform central limit theory and asymptotic confidence sequences	12
Sup-norm adaptive drift estimation for multivariate nonreversible diffusions	12
Algorithmic stability implies training-conditional coverage for distribution-free prediction methods	12
Communication-efficient and distributed-oracle estimation for high-dimensional quantile regression	12
Testing for independence in high dimensions based on empirical copulas	11
Noisy linear inverse problems under convex constraints: Exact risk asymptotics in high dimensions	11
Sharp adaptive and pathwise stable similarity testing for scalar ergodic diffusions	11
Confounder selection via iterative graph expansion	11
Interactive versus noninteractive locally differentially private estimation: Two elbows for the quadratic functional	11
Computational lower bounds for graphon estimation via low-degree polynomials	11
Finite-sample complexity of sequential Monte Carlo estimators	11

A new approach to tests and confidence bands for distribution functions	11
Testing nonparametric shape restrictions	11
Linear biomarker combination for constrained classification	10
Detecting multiple replicating signals using adaptive filtering procedures	10
The distributionally robust prediction error of the LASSO and related estimators	10
Dimension free ridge regression	10
Dispersal density estimation across scales	10
Change acceleration and detection	10
Nonlinear global Fréchet regression for random objects via weak conditional expectation	9
ℓ2 inference for change points in high-dimensional time series via a Two-Way MOSUM	9
Carving model-free inference	9
ARK: Robust knockoffs inference with coupling	9
On universally consistent and fully distribution-free rank tests of vector independence	9
A flexible defense against the winner’s curse	9
The Stein effect for Fréchet means	9
Bridging factor and sparse models	9
On the sample complexity of entropic optimal transport	9
Joint sequential detection and isolation for dependent data streams	8
Local convexity of the TAP free energy and AMP convergence for Z2-synchronization	8
Correction note: “Asymptotic spectral theory for nonlinear time series”	8
Semiparametric inference based on adaptively collected data	8
Conformal inference for random objects	8
Online estimation with rolling validation: Adaptive nonparametric estimation with streaming data	8
Dualizing Le Cam’s method for functional estimation I: General theory	8
Ensemble projection pursuit for general nonparametric regression	7
Affine-equivariant inference for multivariate location under Lp loss functions	7
Entrywise dynamics and universality of general first order methods	7
A general framework to quantify deviations from structural assumptions in the analysis of nonstationary function-valued processes	7
Local permutation tests for conditional independence	7
Adaptive variational Bayes: Optimality, computation and applications	7
Bootstrapping persistent Betti numbers and other stabilizing statistics	7
Matching recovery threshold for correlated random graphs	7
Testing high-dimensional regression coefficients in linear models	7
Asymptotic distributions of largest Pearson correlation coefficients under dependent structures	7
Efficient estimation of the maximal association between multiple predictors and a survival outcome	7
Post-selection inference via algorithmic stability	7
Embedding distributional data	7
Multivariate trend filtering for lattice data	7
Large-dimensional independent component analysis: Statistical optimality and computational tractability	7
Information theoretic limits of robust sub-Gaussian mean estimation under star-shaped constraints	7
Global and individualized community detection in inhomogeneous multilayer networks	7
Symmetry: A general structure in nonparametric regression	7
Spectral analysis of gram matrices with missing at random observations: Convergence, central limit theorems, and applications in statistical inference	7
A nonparametric doubly robust test for a continuous treatment effect	7
Semiparametric Bernstein–von Mises phenomenon via Isotonized Posterior in Wicksell’s problem	6
The online closure principle	6
Rerandomization with diminishing covariate imbalance and diverging number of covariates	6
Optimal signal detection in some spiked random matrix models: Likelihood ratio tests and linear spectral statistics	6
Markov stick-breaking processes	6
Universal regression with adversarial responses	6
Conditional calibration for false discovery rate control under dependence	6
On the existence of powerful p-values and e-values for composite hypotheses	6
Total positivity in multivariate extremes	6
A two-way heterogeneity model for dynamic networks	6
Heavy-tailed Bayesian nonparametric adaptation	6
Some theory about efficient dimension reduction regarding the interaction between two responses	6
Adaptive novelty detection with false discovery rate guarantee	6
Self-normalized Cramér type moderate deviation theorem for Gaussian approximation	6
Asymptotically-exact selective inference for quantile regression	6
Deep neural networks for nonparametric interaction models with diverging dimension	6
Scalable inference in functional linear regression with streaming data	6
Rates of estimation for high-dimensional multireference alignment	6
On robustness and local differential privacy	6
Kurtosis-based projection pursuit for matrix-valued data	6
Estimating a density near an unknown manifold: A Bayesian nonparametric approach	6
Approximation error from discretizations and its applications	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
The curse of overparametrization in adversarial training: Precise analysis of robust generalization for random features regression	5
Semi-supervised U-statistics	5
Grouped variable selection with discrete optimization: Computational and statistical perspectives	5
Convergence of de Finetti’s mixing measure in latent structure models for observed exchangeable sequences	5
A unified analysis of likelihood-based estimators in the Plackett–Luce model	5
Adaptive robust confidence intervals	5
Estimation of the spectral measure from convex combinations of regularly varying random vectors	5
Improved covariance estimation: Optimal robustness and sub-Gaussian guarantees under heavy tails	5
MARS via LASSO	5
One-step estimation of differentiable Hilbert-valued parameters	5
A study of orthogonal array-based designs under a broad class of space-filling criteria	5
Statistical complexity and optimal algorithms for nonlinear ridge bandits	5

Bootstrap-assisted inference for generalized Grenander-type estimators	5
Stereographic Markov chain Monte Carlo	5
Optimal subgroup selection	5
Skewed Bernstein–von Mises theorem and skew-modal approximations	5
A conformal test of linear models via permutation-augmented regressions	5
Gaussian process regression in the flat limit	5
Rate-optimal robust estimation of high-dimensional vector autoregressive models	5
Distributed adaptive Gaussian mean estimation with unknown variance: Interactive protocol helps adaptation	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
Conditional predictive inference for stable algorithms	5
Precise error rates for computationally efficient testing	4
Extreme value inference for heterogeneous power law data	4
Stochastic continuum-armed bandits with additive models: Minimax regrets and adaptive algorithm	4
Uniform consistency in nonparametric mixture models	4
Variable selection, monotone likelihood ratio and group sparsity	4
Optimal heteroskedasticity testing in nonparametric regression	4
Fundamental limits of low-rank matrix estimation with diverging aspect ratios	4
Projective, sparse and learnable latent position network models	4
Statistical inference in tensor completion: Optimal uncertainty quantification and statistical-to-computational gaps	4
Quantile processes and their applications in finite populations	4
A two-step estimating approach for heavy-tailed AR models with nonzero median GARCH-type noises	4
The edge of discovery: Controlling the local false discovery rate at the margin	4
Non-independent component analysis	4
Spectral statistics of sample block correlation matrices	4
Precise asymptotics of bagging regularized M-estimators	4
Generalized multilinear models for sufficient dimension reduction on tensor-valued predictors	4
Early stopping for L2-boosting in high-dimensional linear models	4
StarTrek: Combinatorial variable selection with false discovery rate control	4
Learning low-dimensional nonlinear structures from high-dimensional noisy data: An integral operator approach	4
Unified algorithms for RL with Decision-Estimation Coefficients: PAC, reward-free, preference-based learning and beyond	4
Statistical-computational trade-offs in tensor PCA and related problems via communication complexity	4
Sparse anomaly detection across referentials: A rank-based higher criticism approach	4
Asymptotic normality and optimality in nonsmooth stochastic approximation	4
Testing for practically significant dependencies in high dimensions via bootstrapping maxima of U-statistics	4
A novel statistical approach to analyze image classification	4
Deep approximate policy iteration	4
Finite- and large sample inference for model and coefficients in high-dimensional linear regression with repro samples	4
Tests of missing completely at random based on sample covariance matrices	4
How do noise tails impact on deep ReLU networks?	4
High-dimensional inference for dynamic treatment effects	4
A statistical framework of watermarks for large language models: Pivot, detection efficiency and optimal rules	4
Theory of functional principal component analysis for discretely observed data	4
Exact minimax risk for linear least squares, and the lower tail of sample covariance matrices	4
Tensor factor model estimation by iterative projection	4
Dimension-free mixing times of Gibbs samplers for Bayesian hierarchical models	4
Multivariate root-n-consistent smoothing parameter-free matching estimators and estimators of inverse density weighted expectations	4
Counterfactual inference in sequential experiments	4
On the statistical complexity of sample amplification	4
Gromov–Wasserstein distances: Entropic regularization, duality and sample complexity	4
Random graph asymptotics for treatment effect estimation under network interference	4
Optimal policy evaluation using kernel-based temporal difference methods	4
Concentration of discrepancy-based approximate Bayesian computation via Rademacher complexity	4
The generalization error of max-margin linear classifiers: Benign overfitting and high dimensional asymptotics in the overparametrized regime	4
The impacts of unobserved covariates on covariate-adaptive randomized experiments	3
Optimal nonparametric testing of Missing Completely At Random and its connections to compatibility	3
Precise statistical analysis of classification accuracies for adversarial training	3
Graphical models for nonstationary time series	3
Complexity analysis of Bayesian learning of high-dimensional DAG models and their equivalence classes	3
Higher-order entrywise eigenvectors analysis of low-rank random matrices: Bias correction, Edgeworth expansion and bootstrap	3
Generalization error bounds of dynamic treatment regimes in penalized regression-based learning	3
Covariance estimation under one-bit quantization	3
Settling the sample complexity of model-based offline reinforcement learning	3
Higher-order coverage errors of batching methods via Edgeworth expansions on t-statistics	3
Robust transfer learning with unreliable source data	3
Approximate kernel PCA: Computational versus statistical trade-off	3
Versatile differentially private learning for general loss functions	3
Conditional sequential Monte Carlo in high dimensions	3
Characterizing the SLOPE trade-off: A variational perspective and the Donoho–Tanner limit	3
Semiparametric modeling and analysis for longitudinal network data	3
A CLT for second difference estimators with an application to volatility and intensity	3
Sparse PCA: A new scalable estimator based on integer programming	3
Causality pursuit from heterogeneous environments via neural adversarial invariance learning	3
Increasing dimension asymptotics for two-way crossed mixed effect models	3
A cross-validation framework for signal denoising with applications to trend filtering, dyadic CART and beyond	3
Optimality of approximate message passing for spiked matrix models with rotationally invariant noise	3
A statistical framework for analyzing shape in a time series of random geometric objects	3
Berry–Esseen bounds for design-based causal inference with possibly diverging treatment levels and varying group sizes	3
Low-degree hardness of detection for correlated Erdős–Rényi graphs	3
Parameter estimation in nonlinear multivariate stochastic differential equations based on splitting schemes	3
Pseudo-Labeling for kernel ridge regression under covariate shift	3
On the robustness of minimum norm interpolators and regularized empirical risk minimizers	3
Continuous-time targeted minimum loss-based estimation of intervention-specific mean outcomes	3
Statistical inference for low-rank tensors: Heteroskedasticity, subgaussianity, and applications	3
Online estimation and inference for robust policy evaluation in reinforcement learning	3
Sharp global convergence guarantees for iterative nonconvex optimization with random data	3
Average partial effect estimation using double machine learning	3
Optimization hierarchy for fair statistical decision problems	3
AutoRegressive approximations to nonstationary time series with inference and applications	3
Simplex quantile regression without crossing	3
Distributionally robust learning for multisource unsupervised domain adaptation	3
Inference for extremal regression with dependent heavy-tailed data	3
On blockwise and reference panel-based estimators for genetic data prediction in high dimensions	3
Metric statistics: Exploration and inference for random objects with distance profiles	3
Clustering by hill-climbing: Consistency results	3