Annals of Statistics

Article	Citations
On high-dimensional Poisson models with measurement error: Hypothesis testing for nonlinear nonconvex optimization	136
Estimation and inference for minimizer and minimum of convex functions: Optimality, adaptivity and uncertainty principles	84
A sieve stochastic gradient descent estimator for online nonparametric regression in Sobolev ellipsoids	72
Inference in Ising models on dense regular graphs	70
Efficiency in local differential privacy	68
Robust k-means clustering for distributions with two moments	68
Measuring dependence in the Wasserstein distance for Bayesian nonparametric models	64
Half-trek criterion for identifiability of latent variable models	52
Online inference with multi-modal likelihood functions	42
Universal rank inference via residual subsampling with application to large networks	41
Foundations of structural causal models with cycles and latent variables	35
Scalable estimation and inference for censored quantile regression process	33
Parametric copula adjusted for non- and semiparametric regression	33
Deep learning for the partially linear Cox model	32
Learning sparse graphons and the generalized Kesten–Stigum threshold	31
A general characterization of optimal tie-breaker designs	31
Adaptive and robust multi-task learning	29
Asymptotic distributions of high-dimensional distance correlation inference	28
Consistent inference for diffusions from low frequency measurements	27
Inference for low-rank tensors—no need to debias	26
Inference for low-rank models	26
Asymptotic analysis of synchrosqueezing transform—toward statistical inference with nonlinear-type time-frequency analysis	26
Community detection with dependent connectivity	26
Admissible ways of merging p-values under arbitrary dependence	25
Rate-optimal estimation of mixed semimartingales	24

Uniform convergence of local Fréchet regression with applications to locating extrema and time warping for metric space valued trajectories	24
Refined Cramér-type moderate deviation theorems for general self-normalized sums with applications to dependent random variables and winsorized mean	22
Order-of-addition orthogonal arrays to study the effect of treatment ordering	22
Nonparametric classification with missing data	22
Environment invariant linear least squares	22
Supervised homogeneity fusion: A combinatorial approach	21
Sharp optimality for high-dimensional covariance testing under sparse signals	21
Testing goodness-of-fit and conditional independence with approximate co-sufficient sampling	21
On posterior consistency of data assimilation with Gaussian process priors: The 2D-Navier–Stokes equations	21
Rank and factor loadings estimation in time series tensor factor model by pre-averaging	20
Spectral estimation of Hawkes processes from count data	20
Consistent order selection for ARFIMA processes	20
A causal bootstrap	19
Is infinity that far? A Bayesian nonparametric perspective of finite mixture models	19
Change-point inference in high-dimensional regression models under temporal dependence	19
Limiting distributions for eigenvalues of sample correlation matrices from heavy-tailed populations	19
Spatial dependence and space–time trend in extreme events	18
A nonparametric test for elliptical distribution based on kernel embedding of probabilities	18
New Edgeworth-type expansions with finite sample guarantees	18
Wilks’ theorem for semiparametric regressions with weakly dependent data	18
General spatio-temporal factor models for high-dimensional random fields on a lattice	17
Iterative algorithm for discrete structure recovery	17
Plugin estimation of smooth optimal transport maps	17
Toward theoretical understandings of robust Markov decision processes: Sample complexity and asymptotics	17
Consistency of Bayesian inference for multivariate max-stable distributions	17
Computational lower bounds for graphon estimation via low-degree polynomials	16
Sup-norm adaptive drift estimation for multivariate nonreversible diffusions	16
Learning mixtures of permutations: Groups of pairwise comparisons and combinatorial method of moments	16
Time-uniform central limit theory and asymptotic confidence sequences	16
Distributed nonparametric function estimation: Optimal rate of convergence and cost of adaptation	16
Consistency of invariance-based randomization tests	15
Optimal rates for independence testing via U-statistic permutation tests	15
Wald tests when restrictions are locally singular	15
Backfitting for large scale crossed random effects regressions	15
A shrinkage principle for heavy-tailed data: High-dimensional robust low-rank matrix recovery	15
The Lasso with general Gaussian designs with applications to hypothesis testing	14
Minimax rate of distribution estimation on unknown submanifolds under adversarial losses	14
Surprises in high-dimensional ridgeless least squares interpolation	14
Edgeworth expansions for network moments	14
Projected state-action balancing weights for offline reinforcement learning	14
Detecting multiple replicating signals using adaptive filtering procedures	13
Minimax nonparametric estimation of pure quantum states	13
Testing for independence in high dimensions based on empirical copulas	13
Transfer learning for contextual multi-armed bandits	13
Linear biomarker combination for constrained classification	13
A new approach to tests and confidence bands for distribution functions	13
On least squares estimation under heteroscedastic and heavy-tailed errors	12
Sharp adaptive and pathwise stable similarity testing for scalar ergodic diffusions	12
Dimension free ridge regression	12
Testing nonparametric shape restrictions	12

Interactive versus noninteractive locally differentially private estimation: Two elbows for the quadratic functional	12
Change acceleration and detection	12
Noisy linear inverse problems under convex constraints: Exact risk asymptotics in high dimensions	12
Confidence regions near singular information and boundary points with applications to mixed models	12
Carving model-free inference	11
Finite-sample complexity of sequential Monte Carlo estimators	11
Dispersal density estimation across scales	11
Approximate Message Passing algorithms for rotationally invariant matrices	11
On universally consistent and fully distribution-free rank tests of vector independence	11
Adaptive transfer learning	11
Testing community structure for hypergraphs	11
ℓ2 inference for change points in high-dimensional time series via a Two-Way MOSUM	10
ARK: Robust knockoffs inference with coupling	10
Ridge regression revisited: Debiasing, thresholding and bootstrap	10
On the sample complexity of entropic optimal transport	10
The Stein effect for Fréchet means	10
Learning models with uniform performance via distributionally robust optimization	10
Adaptive estimation in multivariate response regression with hidden variables	10
Tensor clustering with planted structures: Statistical optimality and computational limits	10
Nonlinear global Fréchet regression for random objects via weak conditional expectation	10
Marginal singularity and the benefits of labels in covariate-shift	10
Bridging factor and sparse models	9
Joint sequential detection and isolation for dependent data streams	9
Statistical inference for principal components of spiked covariance matrices	9
Sparse high-dimensional linear regression. Estimating squared error and a phase transition	9
Correction note: “Asymptotic spectral theory for nonlinear time series”	9
Testing high-dimensional regression coefficients in linear models	9
Large-dimensional independent component analysis: Statistical optimality and computational tractability	9
Matching recovery threshold for correlated random graphs	9
Local convexity of the TAP free energy and AMP convergence for Z2-synchronization	9
Existence and uniqueness of the Kronecker covariance MLE	9
SuperMix: Sparse regularization for mixtures	9
Heavy-tailed Bayesian nonparametric adaptation	8
On robustness and local differential privacy	8
Analysis of generalized Bregman surrogate algorithms for nonsmooth nonconvex statistical learning	8
Inference for a two-stage enrichment design	8
Multivariate trend filtering for lattice data	8
A nonparametric doubly robust test for a continuous treatment effect	8
Affine-equivariant inference for multivariate location under Lp loss functions	8
Rerandomization with diminishing covariate imbalance and diverging number of covariates	8
Global and individualized community detection in inhomogeneous multilayer networks	8
Ensemble projection pursuit for general nonparametric regression	8
Spectral analysis of gram matrices with missing at random observations: Convergence, central limit theorems, and applications in statistical inference	8
Adaptive variational Bayes: Optimality, computation and applications	8
Bootstrapping persistent Betti numbers and other stabilizing statistics	7
Peskun–Tierney ordering for Markovian Monte Carlo: Beyond the reversible scenario	7
The online closure principle	7
Two-level parallel flats designs	7
General and feasible tests with multiply-imputed datasets	7
Universal regression with adversarial responses	7
Post-selection inference via algorithmic stability	7
Local permutation tests for conditional independence	7
Estimating a density near an unknown manifold: A Bayesian nonparametric approach	7
Rates of estimation for high-dimensional multireference alignment	7
Adaptive novelty detection with false discovery rate guarantee	7
Optimal signal detection in some spiked random matrix models: Likelihood ratio tests and linear spectral statistics	7
Efficient estimation of the maximal association between multiple predictors and a survival outcome	7
Embedding distributional data	7
A general framework to quantify deviations from structural assumptions in the analysis of nonstationary function-valued processes	7
Optimal false discovery rate control for large scale multiple testing with auxiliary information	7
Some theory about efficient dimension reduction regarding the interaction between two responses	7
Total positivity in multivariate extremes	7
Approximation error from discretizations and its applications	6
Statistical inference in sparse high-dimensional additive models	6
Grouped variable selection with discrete optimization: Computational and statistical perspectives	6
Estimation of the spectral measure from convex combinations of regularly varying random vectors	6
Rate-optimal robust estimation of high-dimensional vector autoregressive models	6
Improved covariance estimation: Optimal robustness and sub-Gaussian guarantees under heavy tails	6
S-estimation in linear models with structured covariance matrices	6
Stereographic Markov chain Monte Carlo	6
Bootstrap-assisted inference for generalized Grenander-type estimators	6
Central limit theorem and bootstrap approximation in high dimensions: Near 1/n rates via implicit smoothing	6
Gaussian process regression in the flat limit	6
Statistical complexity and optimal algorithms for nonlinear ridge bandits	6
A new and flexible design construction for orthogonal arrays for modern applications	6
Deep neural networks for nonparametric interaction models with diverging dimension	6
On the existence of powerful p-values and e-values for composite hypotheses	6
Convex regression in multidimensions: Suboptimality of least squares estimators	6
Conditional calibration for false discovery rate control under dependence	6
Conditional predictive inference for stable algorithms	6

On minimax optimality of sparse Bayes predictive density estimates	6
Model selection in the space of Gaussian models invariant by symmetry	6
Optimal subgroup selection	6
Strong selection consistency of Bayesian vector autoregressive models based on a pseudo-likelihood approach	6
One-step estimation of differentiable Hilbert-valued parameters	5
Augmented minimax linear estimation	5
Causal discovery in heavy-tailed models	5
MARS via LASSO	5
A statistical framework of watermarks for large language models: Pivot, detection efficiency and optimal rules	5
Infinite-dimensional gradient-based descent for alpha-divergence minimisation	5
A conformal test of linear models via permutation-augmented regressions	5
Skewed Bernstein–von Mises theorem and skew-modal approximations	5
Distributed adaptive Gaussian mean estimation with unknown variance: Interactive protocol helps adaptation	5
False discovery rate control with unknown null distribution: Is it possible to mimic the oracle?	5
Boosted nonparametric hazards with time-dependent covariates	5
Extreme value inference for heterogeneous power law data	5
Editorial: Memorial issue for Charles Stein	5
Consistent nonparametric estimation for heavy-tailed sparse graphs	5
A study of orthogonal array-based designs under a broad class of space-filling criteria	5
Convergence of de Finetti’s mixing measure in latent structure models for observed exchangeable sequences	5
Variable selection consistency of Gaussian process regression	5
The curse of overparametrization in adversarial training: Precise analysis of robust generalization for random features regression	5
Stein’s method of normal approximation: Some recollections and reflections	5
Learning low-dimensional nonlinear structures from high-dimensional noisy data: An integral operator approach	5
High-dimensional inference for dynamic treatment effects	4
The generalization error of max-margin linear classifiers: Benign overfitting and high dimensional asymptotics in the overparametrized regime	4
Early stopping for L2-boosting in high-dimensional linear models	4
Spectral statistics of sample block correlation matrices	4
The edge of discovery: Controlling the local false discovery rate at the margin	4
Statistical guarantees for Bayesian uncertainty quantification in nonlinear inverse problems with Gaussian process priors	4
Optimal difference-based variance estimators in time series: A general framework	4
Optimality of spectral clustering in the Gaussian mixture model	4
Higher criticism to compare two large frequency tables, with sensitivity to possible rare and weak differences	4
Integrative methods for post-selection inference under convex constraints	4
Random graph asymptotics for treatment effect estimation under network interference	4
Non-independent component analysis	4
Deep approximate policy iteration	4
Concentration of discrepancy-based approximate Bayesian computation via Rademacher complexity	4
How do noise tails impact on deep ReLU networks?	4
On cross-validated Lasso in high dimensions	4
Precise error rates for computationally efficient testing	4
Total positivity in exponential families with application to binary variables	4
Isotonic regression with unknown permutations: Statistics, computation and adaptation	4
Optimal policy evaluation using kernel-based temporal difference methods	4
Evidence factors from multiple, possibly invalid, instrumental variables	3
On blockwise and reference panel-based estimators for genetic data prediction in high dimensions	3
Approximate kernel PCA: Computational versus statistical trade-off	3
Stochastic continuum-armed bandits with additive models: Minimax regrets and adaptive algorithm	3
Optimal change-point estimation in time series	3
Propriety of the reference posterior distribution in Gaussian process modeling	3
Unified algorithms for RL with Decision-Estimation Coefficients: PAC, reward-free, preference-based learning and beyond	3
Uniform consistency in nonparametric mixture models	3
On statistical learning of simplices: Unmixing problem revisited	3
Empirical tail copulas for functional data	3
Testing equivalence of clustering	3
Semiparametric optimal estimation with nonignorable nonresponse data	3
Covariance estimation under one-bit quantization	3
Variable selection, monotone likelihood ratio and group sparsity	3
Functional sufficient dimension reduction through average Fréchet derivatives	3
On the statistical complexity of sample amplification	3
Higher-order coverage errors of batching methods via Edgeworth expansions on t-statistics	3
Set structured global empirical risk minimizers are rate optimal in general dimensions	3
Powerful knockoffs via minimizing reconstructability	3
Testing for practically significant dependencies in high dimensions via bootstrapping maxima of U-statistics	3
Optimal heteroskedasticity testing in nonparametric regression	3
Fundamental limits of low-rank matrix estimation with diverging aspect ratios	3
Asymptotic normality and optimality in nonsmooth stochastic approximation	3
Adaptive learning rates for support vector machines working on data with low intrinsic dimension	3
Statistical-computational trade-offs in tensor PCA and related problems via communication complexity	3
Inference for extremal regression with dependent heavy-tailed data	3
Simplex quantile regression without crossing	3
Increasing dimension asymptotics for two-way crossed mixed effect models	3
Robust sub-Gaussian estimation of a mean vector in nearly linear time	3
Projective, sparse and learnable latent position network models	3
Tensor factor model estimation by iterative projection	3
Exact minimax risk for linear least squares, and the lower tail of sample covariance matrices	3
Sparse anomaly detection across referentials: A rank-based higher criticism approach	3
Dimension-free mixing times of Gibbs samplers for Bayesian hierarchical models	3
High-dimensional asymptotics of likelihood ratio tests in the Gaussian sequence model under convex constraints	3
StarTrek: Combinatorial variable selection with false discovery rate control	3
Gromov–Wasserstein distances: Entropic regularization, duality and sample complexity	3
Quantile processes and their applications in finite populations	3
Correction note: “Statistical inference for the mean outcome under a possibly nonunique optimal treatment rule”	3
Multiscale Bayesian survival analysis	3
Extreme conditional expectile estimation in heavy-tailed heteroscedastic regression models	3
Distributed statistical inference for massive data	2
Optimal estimation of high-dimensional Gaussian location mixtures	2
Local Whittle estimation of high-dimensional long-run variance and precision matrices	2
Single index Fréchet regression	2
Erratum: Asymptotic genealogies of interacting particle systems with an application to sequential Monte Carlo	2
Conditional sequential Monte Carlo in high dimensions	2
The impacts of unobserved covariates on covariate-adaptive randomized experiments	2
Reconciling the Gaussian and Whittle likelihood with an application to estimation in the frequency domain	2
On the robustness of minimum norm interpolators and regularized empirical risk minimizers	2
Necessary and sufficient conditions for asymptotically optimal linear prediction of random fields on compact metric spaces	2