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883 papers in stat.TH · page 16
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Algorithm recovers arbitrary Gaussians from unknown truncated samples
Efficient Statistics With Unknown Truncation, Polynomial Time Algorithms, Beyond Gaussians
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Regularized e-processes deliver knowledge-driven anytime-valid inference
Regularized e-processes: anytime valid inference with knowledge-based efficiency gains
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Bayesian forests give consistent clusters under mild separation
Consistency of Graphical Model-based Clustering: Robust Clustering using Bayesian Spanning Forest
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Modified Christoffel function uses graphical sparsity for high-d support inference
A Christoffel-like function for high-dimensional support inference in graphical models
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Fractional derivatives of MGFs recover marginal densities
Using fractional derivatives to derive marginal densities
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Consistent estimator for enzyme rates from product times
Statistical inference for a multiscale stochastic model of enzyme kinetics via propagation of chaos
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MOM estimators bound errors with VC-dimension under finite variance
Error bounds of Median-of-means estimators with VC-dimension
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Node subsampling gives joint distributions for network moments
Multivariate Inference of Network Moments by Subsampling
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Change-of-basis adaptation accelerates smoothing rates in bivariate functional data
Structural adaptation and rate accelerated estimation in bivariate functional data
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Mixture MLE positive at zero boundary with probability 1-1/α
Non-standard boundary behaviour in two-component mixture models
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Sparse SBM node sampling yields Gaussian or Poisson limits for subgraph counts
Statistical inference for subgraph counts and clustering coefficient using network sampling in a sparse Stochastic Block Model framework
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Posteriors for PDE trajectories converge to Gaussians
Bernstein-von Mises theorems for time evolution equations
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Bayes credible intervals cover conservatively in inverse problems
Frequentist Coverage of Bayes Posteriors in Nonlinear Inverse Problems with Gaussian Priors
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Nonconvex points recover Z2 ground truth near exact threshold
Nonconvex landscapes for $\mathbf{Z}_2$ synchronization and graph clustering are benign near exact recovery thresholds
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Borrowing forces stricter threshold in liability-based betting tests
Testing by Betting while Borrowing and Bargaining
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Tuned random features match full MMD rates at sub-quadratic cost
Computational-Statistical Trade-off in Kernel Two-Sample Testing with Random Fourier Features
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DP Top-Two algorithms match BAI sample lower bounds
Differentially Private Best-Arm Identification
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Unbounded DP distributions converge to bounded DP as n grows
Statistical Inference for Privatized Data with Unknown Sample Size
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Combined experimental and external data need distinct identification strategies
Identification strategies for combining an experimental study with external data
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Lifted samplers cap asymptotic variance at twice base level
Theoretical guarantees for lifted samplers
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U-statistic of order b stays within O(b log²(dn)/n) of its projection
Order-Explicit Linearization of High-Dimensional $U$-Statistics
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Stability update approximates debiased Lasso for most coordinates
Stability of a Generalized Debiased Lasso with Applications to Resampling-Based Variable Selection
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LAN property holds for parametric birth-death-move particle model
Parametric estimation and LAN property of the birth-death-move process with mutations
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Fiducial method works for Cox models when MLE fails
Semiparametric fiducial inference for Cox models
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ELBO bounds prove consistent selection of mixture components
Estimating the Number of Components in Finite Mixture Models via Variational Approximation
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Unit-square game fixes sharp prophet inequality constants
Optimal single threshold stopping rules and sharp prophet inequalities
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LASSO matrix solutions inherit low rank from ground truth under RIP
Low solution rank of the matrix LASSO under RIP with consequences for rank-constrained algorithms
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Extended negative binomial recovers Poisson parameters from count data
From Poisson Observations to Fitted Negative Binomial Distribution
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James-Stein estimator reduces detection delay in multi-stream tests
Quickest Change Detection for Multiple Data Streams Using the James-Stein Estimator
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Ridge risk on variance-profile data gets exact high-dim formulas
High-dimensional analysis of ridge regression for non-identically distributed data with a variance profile
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This paper formulates federated differential privacy for transfer learning across…
Federated Transfer Learning with Differential Privacy
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Tracy-Widom laws expand asymptotically in n to the -2/3
Asymptotic Expansions of the Limit Laws of Gaussian and Laguerre (Wishart) Ensembles at the Soft Edge
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GAN mapping converts uniform points into copula samples with error bounds
A Generative Approach to Quasi-Random Sampling from Copulas via Space-Filling Designs
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Conical space-times align with faithful causal models
Characterizing Signalling: Connections between Causal Inference and Space-time Geometry
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Empirical Bayes approximates oracle posterior faster than Bernstein-von Mises
Empirical Bayes in Bayesian learning: understanding a common practice
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Relaxed two-stage method widens quantum estimators for transmittance sensing
Two-stage Quantum Estimation and the Asymptotics of Quantum-enhanced Transmittance Sensing
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Learning ω(log log N) halfspaces takes super-polynomial time
Improved Hardness Results for Learning Intersections of Halfspaces
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Umeyama recovers exact matchings when noise is o(d^{-3}n^{-2/d})
The Umeyama algorithm for matching correlated Gaussian geometric models in the low-dimensional regime
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Multivariate method classifies short time series with missing data
Multivariate Functional Linear Discriminant Analysis for the Classification of Short Time Series with Missing Data
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Covariance scan detects changes without sparsity in high-dimensional regression
Detection and inference of changes in high-dimensional linear regression with non-sparse structures
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Rank-preserving bootstrap refines treatment-effect sampling distribution
Sharp variance estimator and causal bootstrap in stratified randomized experiments
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Larger blocks don't always boost block likelihood estimation
Assessing the Impact of Block Size on Block Likelihood Estimation: A Comparative Study
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Mixture model identifies regime shifts in matrix time series
Mixture Matrix-valued Autoregressive Model
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L2 criterion produces new estimator for exponential rate
Estimation of the rate parameter of the probability distribution on the regression setup
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Rényi divergence keeps spectral estimates stable under frequency outliers
On robustness of Spectral R\'{e}nyi divergence
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Adaptive test gains power on low-rank covariance differences
Rank-adaptive covariance testing with applications to genomics and neuroimaging
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Lloyd's algorithm stays consistent under small perturbations
Consistency of Lloyd's Algorithm Under Perturbations
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Gaussian limits give valid CIs for eigenvector linear forms
Statistical Inference for Linear Functions of Eigenvectors with Small Eigengaps
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Extreme graphical lasso recovers sparse tail graphs
Graphical lasso for extremes
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GMM limits under second-order ID differ by exact vs over ID
Large sample properties of GMM estimators under second-order identification