Annals of Statistics

Article	Citations
Estimation and inference for minimizer and minimum of convex functions: Optimality, adaptivity and uncertainty principles	157
A sieve stochastic gradient descent estimator for online nonparametric regression in Sobolev ellipsoids	96
Inference in Ising models on dense regular graphs	74
Efficiency in local differential privacy	56
Foundations of structural causal models with cycles and latent variables	44
Scalable estimation and inference for censored quantile regression process	41
Half-trek criterion for identifiability of latent variable models	38
Universal rank inference via residual subsampling with application to large networks	37
Parametric copula adjusted for non- and semiparametric regression	37
Measuring dependence in the Wasserstein distance for Bayesian nonparametric models	36
On high-dimensional Poisson models with measurement error: Hypothesis testing for nonlinear nonconvex optimization	34
Online inference with multi-modal likelihood functions	33
Debiased regression adjustment in completely randomized experiments with moderately high-dimensional covariates	31
Learning sparse graphons and the generalized Kesten–Stigum threshold	31
Deep learning for the partially linear Cox model	31
A general characterization of optimal tie-breaker designs	30
Spectral gap bounds for reversible hybrid Gibbs chains	29
Adaptive and robust multi-task learning	29
Asymptotic analysis of synchrosqueezing transform—toward statistical inference with nonlinear-type time-frequency analysis	29
Consistent inference for diffusions from low frequency measurements	28
Inference for low-rank models	26
Uniform convergence of local Fréchet regression with applications to locating extrema and time warping for metric space valued trajectories	26
Inference for low-rank tensors—no need to debias	26
Admissible ways of merging p-values under arbitrary dependence	24
Limiting distributions for eigenvalues of sample correlation matrices from heavy-tailed populations	23

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

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

On minimax optimality of sparse Bayes predictive density estimates	6
On the existence of powerful p-values and e-values for composite hypotheses	6
Stereographic Markov chain Monte Carlo	6
Central limit theorem and bootstrap approximation in high dimensions: Near 1/n rates via implicit smoothing	6
Optimal subgroup selection	6
Skewed Bernstein–von Mises theorem and skew-modal approximations	6
Augmented minimax linear estimation	6
Estimation of the spectral measure from convex combinations of regularly varying random vectors	6
A new and flexible design construction for orthogonal arrays for modern applications	6
A study of orthogonal array-based designs under a broad class of space-filling criteria	5
False discovery rate control with unknown null distribution: Is it possible to mimic the oracle?	5
MARS via LASSO	5
Integrative methods for post-selection inference under convex constraints	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
Learning low-dimensional nonlinear structures from high-dimensional noisy data: An integral operator approach	5
Extreme value inference for heterogeneous power law data	5
Rate-optimal robust estimation of high-dimensional vector autoregressive models	5
Optimality of spectral clustering in the Gaussian mixture model	5
A statistical framework of watermarks for large language models: Pivot, detection efficiency and optimal rules	5
Precise error rates for computationally efficient testing	5
High-dimensional inference for dynamic treatment effects	5
The generalization error of max-margin linear classifiers: Benign overfitting and high dimensional asymptotics in the overparametrized regime	5
Grouped variable selection with discrete optimization: Computational and statistical perspectives	5
One-step estimation of differentiable Hilbert-valued parameters	5
A conformal test of linear models via permutation-augmented regressions	5
Early stopping for L2-boosting in high-dimensional linear models	5
The curse of overparametrization in adversarial training: Precise analysis of robust generalization for random features regression	5
Higher criticism to compare two large frequency tables, with sensitivity to possible rare and weak differences	5
How do noise tails impact on deep ReLU networks?	5
Deep approximate policy iteration	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
Gromov–Wasserstein distances: Entropic regularization, duality and sample complexity	4
Testing for practically significant dependencies in high dimensions via bootstrapping maxima of U-statistics	4
Exact minimax risk for linear least squares, and the lower tail of sample covariance matrices	4
Quantile processes and their applications in finite populations	4
Statistical guarantees for Bayesian uncertainty quantification in nonlinear inverse problems with Gaussian process priors	4
Concentration of discrepancy-based approximate Bayesian computation via Rademacher complexity	4
Spectral statistics of sample block correlation matrices	4
Uniform consistency in nonparametric mixture models	4
Variable selection, monotone likelihood ratio and group sparsity	4
Projective, sparse and learnable latent position network models	4
Testing equivalence of clustering	4
Stochastic continuum-armed bandits with additive models: Minimax regrets and adaptive algorithm	4
Asymptotic normality and optimality in nonsmooth stochastic approximation	4
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
StarTrek: Combinatorial variable selection with false discovery rate control	4
Adaptive learning rates for support vector machines working on data with low intrinsic dimension	4
On the statistical complexity of sample amplification	4
Statistical-computational trade-offs in tensor PCA and related problems via communication complexity	4
Fundamental limits of low-rank matrix estimation with diverging aspect ratios	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
Non-independent component analysis	4
Optimal policy evaluation using kernel-based temporal difference methods	4
Tensor factor model estimation by iterative projection	3
Covariance estimation under one-bit quantization	3
A cross-validation framework for signal denoising with applications to trend filtering, dyadic CART and beyond	3
Reinforcement learning for individual optimal policy from heterogeneous data	3
Parameter estimation in nonlinear multivariate stochastic differential equations based on splitting schemes	3
Simplex quantile regression without crossing	3
Complexity analysis of Bayesian learning of high-dimensional DAG models and their equivalence classes	3
Functional sufficient dimension reduction through average Fréchet derivatives	3
Increasing dimension asymptotics for two-way crossed mixed effect models	3
Robust transfer learning with unreliable source data	3
Sparse anomaly detection across referentials: A rank-based higher criticism approach	3
Inference for extremal regression with dependent heavy-tailed data	3
Dimension reduction for functional data based on weak conditional moments	3
Metric statistics: Exploration and inference for random objects with distance profiles	3
AutoRegressive approximations to nonstationary time series with inference and applications	3
Higher-order entrywise eigenvectors analysis of low-rank random matrices: Bias correction, Edgeworth expansion and bootstrap	3
Choosing between persistent and stationary volatility	3
On an extension of the promotion time cure model	3
High-dimensional asymptotics of likelihood ratio tests in the Gaussian sequence model under convex constraints	3
Evidence factors from multiple, possibly invalid, instrumental variables	3
Approximate kernel PCA: Computational versus statistical trade-off	3
Semiparametric optimal estimation with nonignorable nonresponse data	3
Unified algorithms for RL with Decision-Estimation Coefficients: PAC, reward-free, preference-based learning and beyond	3
Robust sub-Gaussian estimation of a mean vector in nearly linear time	3
Generalization error bounds of dynamic treatment regimes in penalized regression-based learning	3
Online change-point detection for matrix-valued time series with latent two-way factor structure	3
Sharp global convergence guarantees for iterative nonconvex optimization with random data	3
Adaptive estimation of multivariate piecewise polynomials and bounded variation functions by optimal decision trees	3
Empirical partially Bayes multiple testing and compound χ2 decisions	3
Optimization hierarchy for fair statistical decision problems	3
Extreme conditional expectile estimation in heavy-tailed heteroscedastic regression models	3
Multiscale Bayesian survival analysis	3
Higher-order coverage errors of batching methods via Edgeworth expansions on t-statistics	3
Powerful knockoffs via minimizing reconstructability	3
Optimal heteroskedasticity testing in nonparametric regression	3