Annals of Statistics

Article	Citations
Estimation and inference for minimizer and minimum of convex functions: Optimality, adaptivity and uncertainty principles	142
A sieve stochastic gradient descent estimator for online nonparametric regression in Sobolev ellipsoids	84
Inference in Ising models on dense regular graphs	74
Efficiency in local differential privacy	72
Robust k-means clustering for distributions with two moments	67
Scalable estimation and inference for censored quantile regression process	53
Universal rank inference via residual subsampling with application to large networks	42
Deep learning for the partially linear Cox model	36
Foundations of structural causal models with cycles and latent variables	36
Half-trek criterion for identifiability of latent variable models	34
Parametric copula adjusted for non- and semiparametric regression	33
Measuring dependence in the Wasserstein distance for Bayesian nonparametric models	33
Online inference with multi-modal likelihood functions	32
Learning sparse graphons and the generalized Kesten–Stigum threshold	30
On high-dimensional Poisson models with measurement error: Hypothesis testing for nonlinear nonconvex optimization	30
A general characterization of optimal tie-breaker designs	29
Inference for low-rank tensors—no need to debias	28
Uniform convergence of local Fréchet regression with applications to locating extrema and time warping for metric space valued trajectories	28
Consistent inference for diffusions from low frequency measurements	27
Community detection with dependent connectivity	27
Asymptotic distributions of high-dimensional distance correlation inference	26
Adaptive and robust multi-task learning	26
Admissible ways of merging p-values under arbitrary dependence	26
Asymptotic analysis of synchrosqueezing transform—toward statistical inference with nonlinear-type time-frequency analysis	25
Inference for low-rank models	23

Rate-optimal estimation of mixed semimartingales	23
Environment invariant linear least squares	22
Sharp optimality for high-dimensional covariance testing under sparse signals	22
Nonparametric classification with missing data	22
Refined Cramér-type moderate deviation theorems for general self-normalized sums with applications to dependent random variables and winsorized mean	21
On posterior consistency of data assimilation with Gaussian process priors: The 2D-Navier–Stokes equations	21
Supervised homogeneity fusion: A combinatorial approach	21
Change-point inference in high-dimensional regression models under temporal dependence	20
Spectral estimation of Hawkes processes from count data	20
Limiting distributions for eigenvalues of sample correlation matrices from heavy-tailed populations	20
Rank and factor loadings estimation in time series tensor factor model by pre-averaging	20
Order-of-addition orthogonal arrays to study the effect of treatment ordering	19
Is infinity that far? A Bayesian nonparametric perspective of finite mixture models	19
Consistent order selection for ARFIMA processes	19
Testing goodness-of-fit and conditional independence with approximate co-sufficient sampling	19
Wilks’ theorem for semiparametric regressions with weakly dependent data	19
Iterative algorithm for discrete structure recovery	18
New Edgeworth-type expansions with finite sample guarantees	18
The numeraire e-variable and reverse information projection	17
Plugin estimation of smooth optimal transport maps	17
On the convergence of coordinate ascent variational inference	17
Spatial dependence and space–time trend in extreme events	17
Asymptotic distribution of maximum likelihood estimator in generalized linear mixed models with crossed random effects	17
Consistency of Bayesian inference for multivariate max-stable distributions	17
A nonparametric test for elliptical distribution based on kernel embedding of probabilities	16
Distributed nonparametric function estimation: Optimal rate of convergence and cost of adaptation	16
Surprises in high-dimensional ridgeless least squares interpolation	16
General spatio-temporal factor models for high-dimensional random fields on a lattice	16
Projected state-action balancing weights for offline reinforcement learning	16
Learning mixtures of permutations: Groups of pairwise comparisons and combinatorial method of moments	16
Toward theoretical understandings of robust Markov decision processes: Sample complexity and asymptotics	16
The Lasso with general Gaussian designs with applications to hypothesis testing	16
Sup-norm adaptive drift estimation for multivariate nonreversible diffusions	15
Wald tests when restrictions are locally singular	15
Computational lower bounds for graphon estimation via low-degree polynomials	15
Backfitting for large scale crossed random effects regressions	15
Consistency of invariance-based randomization tests	15
Minimax rate for multivariate data under componentwise local differential privacy constraints	15
Time-uniform central limit theory and asymptotic confidence sequences	14
Transfer learning for contextual multi-armed bandits	14
Minimax rate of distribution estimation on unknown submanifolds under adversarial losses	14
Edgeworth expansions for network moments	14
Optimal rates for independence testing via U-statistic permutation tests	14
Linear biomarker combination for constrained classification	13
Minimax nonparametric estimation of pure quantum states	13
Detecting multiple replicating signals using adaptive filtering procedures	13
Testing for independence in high dimensions based on empirical copulas	13
Testing nonparametric shape restrictions	12
Noisy linear inverse problems under convex constraints: Exact risk asymptotics in high dimensions	12
Sharp adaptive and pathwise stable similarity testing for scalar ergodic diffusions	12

On least squares estimation under heteroscedastic and heavy-tailed errors	12
Change acceleration and detection	12
Confidence regions near singular information and boundary points with applications to mixed models	12
Dispersal density estimation across scales	11
Finite-sample complexity of sequential Monte Carlo estimators	11
Dimension free ridge regression	11
The Stein effect for Fréchet means	11
Interactive versus noninteractive locally differentially private estimation: Two elbows for the quadratic functional	11
Adaptive transfer learning	11
A new approach to tests and confidence bands for distribution functions	11
Approximate Message Passing algorithms for rotationally invariant matrices	11
Testing community structure for hypergraphs	11
Marginal singularity and the benefits of labels in covariate-shift	10
On the sample complexity of entropic optimal transport	10
Carving model-free inference	10
Joint sequential detection and isolation for dependent data streams	10
ℓ2 inference for change points in high-dimensional time series via a Two-Way MOSUM	10
ARK: Robust knockoffs inference with coupling	10
Nonlinear global Fréchet regression for random objects via weak conditional expectation	10
Bridging factor and sparse models	10
Ridge regression revisited: Debiasing, thresholding and bootstrap	10
On universally consistent and fully distribution-free rank tests of vector independence	10
Adaptive estimation in multivariate response regression with hidden variables	10
Tensor clustering with planted structures: Statistical optimality and computational limits	10
Correction note: “Asymptotic spectral theory for nonlinear time series”	10
Multivariate trend filtering for lattice data	9
Statistical inference for principal components of spiked covariance matrices	9
Existence and uniqueness of the Kronecker covariance MLE	9
Asymptotic distributions of largest Pearson correlation coefficients under dependent structures	9
Heavy-tailed Bayesian nonparametric adaptation	9
Ensemble projection pursuit for general nonparametric regression	9
The online closure principle	9
Conformal inference for random objects	9
Matching recovery threshold for correlated random graphs	9
Semiparametric inference based on adaptively collected data	9
Analysis of generalized Bregman surrogate algorithms for nonsmooth nonconvex statistical learning	9
Adaptive variational Bayes: Optimality, computation and applications	9
Rerandomization with diminishing covariate imbalance and diverging number of covariates	9
Testing high-dimensional regression coefficients in linear models	9
Large-dimensional independent component analysis: Statistical optimality and computational tractability	9
Local convexity of the TAP free energy and AMP convergence for Z2-synchronization	9
A nonparametric doubly robust test for a continuous treatment effect	9
Affine-equivariant inference for multivariate location under Lp loss functions	9
On robustness and local differential privacy	8
Embedding distributional data	8
A general framework to quantify deviations from structural assumptions in the analysis of nonstationary function-valued processes	8
Sparse high-dimensional linear regression. Estimating squared error and a phase transition	8
Bootstrapping persistent Betti numbers and other stabilizing statistics	8
Post-selection inference via algorithmic stability	8
Global and individualized community detection in inhomogeneous multilayer networks	8
Peskun–Tierney ordering for Markovian Monte Carlo: Beyond the reversible scenario	8
Efficient estimation of the maximal association between multiple predictors and a survival outcome	8
Inference for a two-stage enrichment design	8
Local permutation tests for conditional independence	8
Spectral analysis of gram matrices with missing at random observations: Convergence, central limit theorems, and applications in statistical inference	8
Stereographic Markov chain Monte Carlo	7
Optimal false discovery rate control for large scale multiple testing with auxiliary information	7
Rates of estimation for high-dimensional multireference alignment	7
Optimal signal detection in some spiked random matrix models: Likelihood ratio tests and linear spectral statistics	7
Adaptive novelty detection with false discovery rate guarantee	7
Deep neural networks for nonparametric interaction models with diverging dimension	7
Two-level parallel flats designs	7
Some theory about efficient dimension reduction regarding the interaction between two responses	7
Bootstrap-assisted inference for generalized Grenander-type estimators	7
Convex regression in multidimensions: Suboptimality of least squares estimators	7
Self-normalized Cramér type moderate deviation theorem for Gaussian approximation	7
Estimating a density near an unknown manifold: A Bayesian nonparametric approach	7
General and feasible tests with multiply-imputed datasets	7
Total positivity in multivariate extremes	7
Improved covariance estimation: Optimal robustness and sub-Gaussian guarantees under heavy tails	6
Approximation error from discretizations and its applications	6
S-estimation in linear models with structured covariance matrices	6
Estimation of the spectral measure from convex combinations of regularly varying random vectors	6
A study of orthogonal array-based designs under a broad class of space-filling criteria	6
Augmented minimax linear estimation	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
Optimal subgroup selection	6
On minimax optimality of sparse Bayes predictive density estimates	6
Model selection in the space of Gaussian models invariant by symmetry	6

Distributed adaptive Gaussian mean estimation with unknown variance: Interactive protocol helps adaptation	6
Central limit theorem and bootstrap approximation in high dimensions: Near 1/n rates via implicit smoothing	6
A new and flexible design construction for orthogonal arrays for modern applications	6
Universal regression with adversarial responses	6
Conditional predictive inference for stable algorithms	6
Statistical complexity and optimal algorithms for nonlinear ridge bandits	6
Grouped variable selection with discrete optimization: Computational and statistical perspectives	6
Gaussian process regression in the flat limit	6
Learning low-dimensional nonlinear structures from high-dimensional noisy data: An integral operator approach	5
Skewed Bernstein–von Mises theorem and skew-modal approximations	5
The curse of overparametrization in adversarial training: Precise analysis of robust generalization for random features regression	5
Editorial: Memorial issue for Charles Stein	5
Optimality of spectral clustering in the Gaussian mixture model	5
One-step estimation of differentiable Hilbert-valued parameters	5
Precise error rates for computationally efficient testing	5
MARS via LASSO	5
How do noise tails impact on deep ReLU networks?	5
Stein’s method of normal approximation: Some recollections and reflections	5
High-dimensional inference for dynamic treatment effects	5
Variable selection consistency of Gaussian process regression	5
Boosted nonparametric hazards with time-dependent covariates	5
Optimal policy evaluation using kernel-based temporal difference methods	5
The generalization error of max-margin linear classifiers: Benign overfitting and high dimensional asymptotics in the overparametrized regime	5
A statistical framework of watermarks for large language models: Pivot, detection efficiency and optimal rules	5
Spectral statistics of sample block correlation matrices	5
A conformal test of linear models via permutation-augmented regressions	5
Early stopping for L2-boosting in high-dimensional linear models	5
Infinite-dimensional gradient-based descent for alpha-divergence minimisation	5
Consistent nonparametric estimation for heavy-tailed sparse graphs	5
Integrative methods for post-selection inference under convex constraints	5
False discovery rate control with unknown null distribution: Is it possible to mimic the oracle?	5
Higher criticism to compare two large frequency tables, with sensitivity to possible rare and weak differences	5
Convergence of de Finetti’s mixing measure in latent structure models for observed exchangeable sequences	5
Extreme value inference for heterogeneous power law data	5
Rate-optimal robust estimation of high-dimensional vector autoregressive models	5
Random graph asymptotics for treatment effect estimation under network interference	4
Isotonic regression with unknown permutations: Statistics, computation and adaptation	4
The edge of discovery: Controlling the local false discovery rate at the margin	4
Statistical-computational trade-offs in tensor PCA and related problems via communication complexity	4
Uniform consistency in nonparametric mixture models	4
Gromov–Wasserstein distances: Entropic regularization, duality and sample complexity	4
Adaptive learning rates for support vector machines working on data with low intrinsic dimension	4
Set structured global empirical risk minimizers are rate optimal in general dimensions	4
Empirical tail copulas for functional data	4
Optimal difference-based variance estimators in time series: A general framework	4
Statistical guarantees for Bayesian uncertainty quantification in nonlinear inverse problems with Gaussian process priors	4
StarTrek: Combinatorial variable selection with false discovery rate control	4
Dimension-free mixing times of Gibbs samplers for Bayesian hierarchical models	4
On blockwise and reference panel-based estimators for genetic data prediction in high dimensions	4
Exact minimax risk for linear least squares, and the lower tail of sample covariance matrices	4
Stochastic continuum-armed bandits with additive models: Minimax regrets and adaptive algorithm	4
Testing for practically significant dependencies in high dimensions via bootstrapping maxima of U-statistics	4
Quantile processes and their applications in finite populations	4
Deep approximate policy iteration	4
Non-independent component analysis	4
Concentration of discrepancy-based approximate Bayesian computation via Rademacher complexity	4
On the statistical complexity of sample amplification	4
Projective, sparse and learnable latent position network models	4
Fundamental limits of low-rank matrix estimation with diverging aspect ratios	4
Propriety of the reference posterior distribution in Gaussian process modeling	4
Asymptotic normality and optimality in nonsmooth stochastic approximation	4
Optimal change-point estimation in time series	3
Unified algorithms for RL with Decision-Estimation Coefficients: PAC, reward-free, preference-based learning and beyond	3
Correction note: “Statistical inference for the mean outcome under a possibly nonunique optimal treatment rule”	3
Sparse anomaly detection across referentials: A rank-based higher criticism approach	3
Evidence factors from multiple, possibly invalid, instrumental variables	3
Online change-point detection for matrix-valued time series with latent two-way factor structure	3
Metric statistics: Exploration and inference for random objects with distance profiles	3
AutoRegressive approximations to nonstationary time series with inference and applications	3
On an extension of the promotion time cure model	3
Multiscale Bayesian survival analysis	3
Extreme conditional expectile estimation in heavy-tailed heteroscedastic regression models	3
Semiparametric optimal estimation with nonignorable nonresponse data	3
Optimal heteroskedasticity testing in nonparametric regression	3
Inference for extremal regression with dependent heavy-tailed data	3
Testing equivalence of clustering	3
Robust sub-Gaussian estimation of a mean vector in nearly linear time	3
A statistical framework for analyzing shape in a time series of random geometric objects	3
Complexity analysis of Bayesian learning of high-dimensional DAG models and their equivalence classes	3
Sharp global convergence guarantees for iterative nonconvex optimization with random data	3
Empirical partially Bayes multiple testing and compound χ2 decisions	3
Optimization hierarchy for fair statistical decision problems	3
Approximate kernel PCA: Computational versus statistical trade-off	3
Choosing between persistent and stationary volatility	3
Increasing dimension asymptotics for two-way crossed mixed effect models	3
Tensor factor model estimation by iterative projection	3
Variable selection, monotone likelihood ratio and group sparsity	3
Functional sufficient dimension reduction through average Fréchet derivatives	3
Generalization error bounds of dynamic treatment regimes in penalized regression-based learning	3
Adaptive estimation of multivariate piecewise polynomials and bounded variation functions by optimal decision trees	3
A cross-validation framework for signal denoising with applications to trend filtering, dyadic CART and beyond	3
Parameter estimation in nonlinear multivariate stochastic differential equations based on splitting schemes	3
Simplex quantile regression without crossing	3
Dimension reduction for functional data based on weak conditional moments	3
Covariance estimation under one-bit quantization	3