Annals of Statistics

Article	Citations
A sieve stochastic gradient descent estimator for online nonparametric regression in Sobolev ellipsoids	160
Estimation and inference for minimizer and minimum of convex functions: Optimality, adaptivity and uncertainty principles	103
Inference in Ising models on dense regular graphs	78
Efficiency in local differential privacy	43
On high-dimensional Poisson models with measurement error: Hypothesis testing for nonlinear nonconvex optimization	40
Scalable estimation and inference for censored quantile regression process	37
Debiased regression adjustment in completely randomized experiments with moderately high-dimensional covariates	37
Universal rank inference via residual subsampling with application to large networks	35
Online inference with multi-modal likelihood functions	35
Parametric copula adjusted for non- and semiparametric regression	32
Half-trek criterion for identifiability of latent variable models	31
Learning sparse graphons and the generalized Kesten–Stigum threshold	30
Spectral gap bounds for reversible hybrid Gibbs chains	30
A general characterization of optimal tie-breaker designs	30
Deep learning for the partially linear Cox model	30
Admissible ways of merging p-values under arbitrary dependence	29
Inference for low-rank tensors—no need to debias	27
Consistent inference for diffusions from low frequency measurements	25
Adaptive and robust multi-task learning	24
Inference for low-rank models	23
Uniform convergence of local Fréchet regression with applications to locating extrema and time warping for metric space valued trajectories	23
Asymptotic analysis of synchrosqueezing transform—toward statistical inference with nonlinear-type time-frequency analysis	23
Sharp optimality for high-dimensional covariance testing under sparse signals	22
Rate-optimal estimation of mixed semimartingales	22
Environment invariant linear least squares	22

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

Confidence regions near singular information and boundary points with applications to mixed models	11
Interactive versus noninteractive locally differentially private estimation: Two elbows for the quadratic functional	11
A new approach to tests and confidence bands for distribution functions	11
Adaptive transfer learning	11
Noisy linear inverse problems under convex constraints: Exact risk asymptotics in high dimensions	11
On least squares estimation under heteroscedastic and heavy-tailed errors	11
Dimension free ridge regression	11
Testing community structure for hypergraphs	10
Dispersal density estimation across scales	10
Nonlinear global Fréchet regression for random objects via weak conditional expectation	10
Approximate Message Passing algorithms for rotationally invariant matrices	10
ℓ2 inference for change points in high-dimensional time series via a Two-Way MOSUM	10
ARK: Robust knockoffs inference with coupling	10
Carving model-free inference	10
The Stein effect for Fréchet means	10
Ridge regression revisited: Debiasing, thresholding and bootstrap	10
Marginal singularity and the benefits of labels in covariate-shift	9
On the sample complexity of entropic optimal transport	9
On universally consistent and fully distribution-free rank tests of vector independence	9
Entrywise dynamics and universality of general first order methods	9
Adaptive estimation in multivariate response regression with hidden variables	9
Correction note: “Asymptotic spectral theory for nonlinear time series”	9
Semiparametric inference based on adaptively collected data	9
Joint sequential detection and isolation for dependent data streams	9
Tensor clustering with planted structures: Statistical optimality and computational limits	9
Bridging factor and sparse models	9
Conformal inference for random objects	9
Asymptotic distributions of largest Pearson correlation coefficients under dependent structures	9
Testing high-dimensional regression coefficients in linear models	9
Large-dimensional independent component analysis: Statistical optimality and computational tractability	8
A nonparametric doubly robust test for a continuous treatment effect	8
Local convexity of the TAP free energy and AMP convergence for Z2-synchronization	8
Heavy-tailed Bayesian nonparametric adaptation	8
Adaptive variational Bayes: Optimality, computation and applications	8
Bootstrapping persistent Betti numbers and other stabilizing statistics	8
Analysis of generalized Bregman surrogate algorithms for nonsmooth nonconvex statistical learning	8
Statistical inference for principal components of spiked covariance matrices	8
Affine-equivariant inference for multivariate location under Lp loss functions	8
Rerandomization with diminishing covariate imbalance and diverging number of covariates	8
Local permutation tests for conditional independence	8
Matching recovery threshold for correlated random graphs	8
Multivariate trend filtering for lattice data	8
Ensemble projection pursuit for general nonparametric regression	8
Sparse high-dimensional linear regression. Estimating squared error and a phase transition	8
Global and individualized community detection in inhomogeneous multilayer networks	8
Spectral analysis of gram matrices with missing at random observations: Convergence, central limit theorems, and applications in statistical inference	7
The online closure principle	7
Self-normalized Cramér type moderate deviation theorem for Gaussian approximation	7
Optimal false discovery rate control for large scale multiple testing with auxiliary information	7
A general framework to quantify deviations from structural assumptions in the analysis of nonstationary function-valued processes	7
Embedding distributional data	7
Post-selection inference via algorithmic stability	7
Optimal signal detection in some spiked random matrix models: Likelihood ratio tests and linear spectral statistics	7
Estimating a density near an unknown manifold: A Bayesian nonparametric approach	7
Efficient estimation of the maximal association between multiple predictors and a survival outcome	7
On robustness and local differential privacy	7
Some theory about efficient dimension reduction regarding the interaction between two responses	7
General and feasible tests with multiply-imputed datasets	7
Rates of estimation for high-dimensional multireference alignment	7
S-estimation in linear models with structured covariance matrices	6
Total positivity in multivariate extremes	6
Bootstrap-assisted inference for generalized Grenander-type estimators	6
On the existence of powerful p-values and e-values for composite hypotheses	6
Conditional calibration for false discovery rate control under dependence	6
Deep neural networks for nonparametric interaction models with diverging dimension	6
Universal regression with adversarial responses	6
Stereographic Markov chain Monte Carlo	6
Improved covariance estimation: Optimal robustness and sub-Gaussian guarantees under heavy tails	6
Optimal subgroup selection	6
A new and flexible design construction for orthogonal arrays for modern applications	6
Adaptive novelty detection with false discovery rate guarantee	6
Approximation error from discretizations and its applications	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
MARS via LASSO	5
On minimax optimality of sparse Bayes predictive density estimates	5
Rate-optimal robust estimation of high-dimensional vector autoregressive models	5
Augmented minimax linear estimation	5
Extreme value inference for heterogeneous power law data	5
The curse of overparametrization in adversarial training: Precise analysis of robust generalization for random features regression	5

Distributed adaptive Gaussian mean estimation with unknown variance: Interactive protocol helps adaptation	5
Estimation of the spectral measure from convex combinations of regularly varying random vectors	5
Conditional predictive inference for stable algorithms	5
Statistical complexity and optimal algorithms for nonlinear ridge bandits	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
How do noise tails impact on deep ReLU networks?	5
False discovery rate control with unknown null distribution: Is it possible to mimic the oracle?	5
Model selection in the space of Gaussian models invariant by symmetry	5
A study of orthogonal array-based designs under a broad class of space-filling criteria	5
Gaussian process regression in the flat limit	5
Grouped variable selection with discrete optimization: Computational and statistical perspectives	5
A conformal test of linear models via permutation-augmented regressions	5
Early stopping for L2-boosting in high-dimensional linear models	5
One-step estimation of differentiable Hilbert-valued parameters	5
Convergence of de Finetti’s mixing measure in latent structure models for observed exchangeable sequences	5
Skewed Bernstein–von Mises theorem and skew-modal approximations	5
Statistical guarantees for Bayesian uncertainty quantification in nonlinear inverse problems with Gaussian process priors	4
Adaptive learning rates for support vector machines working on data with low intrinsic dimension	4
Learning low-dimensional nonlinear structures from high-dimensional noisy data: An integral operator approach	4
The edge of discovery: Controlling the local false discovery rate at the margin	4
Stochastic continuum-armed bandits with additive models: Minimax regrets and adaptive algorithm	4
Testing equivalence of clustering	4
Gromov–Wasserstein distances: Entropic regularization, duality and sample complexity	4
Asymptotic normality and optimality in nonsmooth stochastic approximation	4
Dimension-free mixing times of Gibbs samplers for Bayesian hierarchical models	4
Random graph asymptotics for treatment effect estimation under network interference	4
Non-independent component analysis	4
Spectral statistics of sample block correlation matrices	4
High-dimensional inference for dynamic treatment effects	4
Optimal policy evaluation using kernel-based temporal difference methods	4
Uniform consistency in nonparametric mixture models	4
On blockwise and reference panel-based estimators for genetic data prediction in high dimensions	4
StarTrek: Combinatorial variable selection with false discovery rate control	4
Fundamental limits of low-rank matrix estimation with diverging aspect ratios	4
On the statistical complexity of sample amplification	4
Optimal difference-based variance estimators in time series: A general framework	4
Concentration of discrepancy-based approximate Bayesian computation via Rademacher complexity	4
Deep approximate policy iteration	4
The generalization error of max-margin linear classifiers: Benign overfitting and high dimensional asymptotics in the overparametrized regime	4
Higher criticism to compare two large frequency tables, with sensitivity to possible rare and weak differences	4
Quantile processes and their applications in finite populations	4
Variable selection, monotone likelihood ratio and group sparsity	4
Projective, sparse and learnable latent position network models	4
Statistical-computational trade-offs in tensor PCA and related problems via communication complexity	4
Exact minimax risk for linear least squares, and the lower tail of sample covariance matrices	4
Testing for practically significant dependencies in high dimensions via bootstrapping maxima of U-statistics	4
Isotonic regression with unknown permutations: Statistics, computation and adaptation	4
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
High-dimensional asymptotics of likelihood ratio tests in the Gaussian sequence model under convex constraints	3
Adaptive test of independence based on HSIC measures	3
Metric statistics: Exploration and inference for random objects with distance profiles	3
AutoRegressive approximations to nonstationary time series with inference and applications	3
Empirical partially Bayes multiple testing and compound χ2 decisions	3
Optimization hierarchy for fair statistical decision problems	3
Sharp global convergence guarantees for iterative nonconvex optimization with random data	3
Functional sufficient dimension reduction through average Fréchet derivatives	3
Approximate kernel PCA: Computational versus statistical trade-off	3
Robust transfer learning with unreliable source data	3
Tensor factor model estimation by iterative projection	3
Inference for extremal regression with dependent heavy-tailed data	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
Online change-point detection for matrix-valued time series with latent two-way factor structure	3
A cross-validation framework for signal denoising with applications to trend filtering, dyadic CART and beyond	3
On an extension of the promotion time cure model	3
Choosing between persistent and stationary volatility	3
Extreme conditional expectile estimation in heavy-tailed heteroscedastic regression models	3
Evidence factors from multiple, possibly invalid, instrumental variables	3
Multiscale Bayesian survival analysis	3
Sparse anomaly detection across referentials: A rank-based higher criticism approach	3
Unified algorithms for RL with Decision-Estimation Coefficients: PAC, reward-free, preference-based learning and beyond	3
Covariance estimation under one-bit quantization	3
Complexity analysis of Bayesian learning of high-dimensional DAG models and their equivalence classes	3
Semiparametric modeling and analysis for longitudinal network data	3
Higher-order entrywise eigenvectors analysis of low-rank random matrices: Bias correction, Edgeworth expansion and bootstrap	3
Reinforcement learning for individual optimal policy from heterogeneous data	3
Generalization error bounds of dynamic treatment regimes in penalized regression-based learning	3
Parameter estimation in nonlinear multivariate stochastic differential equations based on splitting schemes	3
Dimension reduction for functional data based on weak conditional moments	3
Simplex quantile regression without crossing	3