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883 papers in stat.TH · page 15
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Trajectory fitting recovers drift in singular Volterra equations
Drift estimation for rough processes under small noise asymptotic : trajectory fitting method
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Diffusion models learn high-variance modes first via inverse scaling
An Analytical Theory of Spectral Bias in the Learning Dynamics of Diffusion Models
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Path regularization bounds generalization error in finite deep nets
Path Regularization: A Near-Complete and Optimal Nonasymptotic Generalization Theory for Multilayer Neural Networks and Double Descent Phenomenon
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Single-index model achieves 1D optimal rates for batched bandits
Batched Single-Index Global Multi-Armed Bandits with Covariates
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Exact multi-graph alignment possible above critical threshold
The feasibility of multi-graph alignment: a Bayesian approach
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Multi-graph alignment has sharp all-or-nothing threshold in Gaussian model
The feasibility of multi-graph alignment: a Bayesian approach
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MinimaxSplit trees bound excess risk by worst-case child impurities
Stabilizing the Splits through Minimax Decision Trees
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Bias-corrected top-two stats give consistent extreme estimates
Extreme Value Analysis based on Blockwise Top-Two Order Statistics
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Low-degree polynomials fail below BBP and Kesten-Stigum thresholds
Sharp Phase Transitions in Estimation with Low-Degree Polynomials
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Nyström MMD test matches minimax optimal separation rate
A Scalable Nystrom-Based Kernel Two-Sample Test with Permutations
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LLMs can drive hallucination probability to near zero with better data
Hallucinations are inevitable but can be made statistically negligible
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Dirichlet-kernel Gasser-Müller estimator introduced for simplex regression
On the Dirichlet-kernel Gasser--M\"uller estimator and its competitors for fixed design regression on the simplex
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SGD multiplier bootstrap hits 1/sqrt(n) convex distance rate
Gaussian Approximation and Multiplier Bootstrap for Stochastic Gradient Descent
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L1 quantile process convergence requires local absolute continuity
A necessary and sufficient condition for convergence in distribution of the quantile process in $L^1(0,1)$
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Point cloud estimators for Minkowski tensors become asymptotically unbiased
Minkowski tensors for point clouds and voxelized data: robust, asymptotically unbiased estimators
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Log-likelihood strongly concave near true tree parameters
Likelihood landscape of binary latent model on a tree
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Heat split into two parts tracks free-energy gain in driven dot
Heat-dissipation decomposition and free-energy generation in a non-equilibrium dot with multi-electron states
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Kernel estimators recover varifolds from point samples
A varifold-type estimation for data sampled on a rectifiable set
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Minimum Hellinger distance estimators can be made private under a new Hellinger…
Private Minimum Hellinger Distance Estimation via Hellinger Distance Differential Privacy
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Bayesian optimal transport partitions sphere for local regressions
Bayesian Sphere-on-Sphere Regression with Optimal Transport Maps
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Unified method yields valid confidence sets for stochastic optimization
Honest Inference for Stochastic Optimization
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Noisy SIS epidemic mixes in Theta(n log n) time
Mixing time for an epidemic model on graphs with external sources of infection
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Pairwise classification learns ordered smooth boundaries with ReLU nets
Statistical learnability of smooth boundaries via pairwise binary classification with deep ReLU networks
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Copula loss lifts Vision Transformer performance on both-eye myopia scans
Copula-enhanced Vision Transformer for high myopia diagnosis through OU UWF fundus images
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Swapping test controls Type I error exactly for conditional independence
Testing conditional independence under isotonicity
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Persistent homology yields stable time-series similarity score
A Stable Measure of Similarity for Time Series using Persistent Homology
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ESPRIT DoA estimates become inconsistent for large arrays
A Large-Dimensional Analysis of ESPRIT DoA Estimation: Inconsistency and a Correction via RMT
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A necessary and sufficient condition determines size controllability for…
A Necessary and Sufficient Condition for Size Controllability of Heteroskedasticity Robust Test Statistics
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Rescaled entropic self-transport converges to score function
The entropic optimal (self-)transport problem: Limit distributions for decreasing regularization with application to score function estimation
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Probit and logit DA samplers mix in linear time with sample size
Fast Mixing of Data Augmentation Algorithms: Bayesian Probit, Logit, and Lasso Regression
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Known strata distributions still leave principal causal effects only partially identified
Partial identification of principal causal effects under violations of principal ignorability
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DM embedding error decays as (log n/n) to 1/(8d+16)
How well behaved is finite dimensional Diffusion Maps?
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Generalized ψ-estimators admit monotone decreasing form
Monotone representation and measurability of generalized $\psi$-estimators
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Coin betting is optimal for e-variable mean testing
On the optimality of coin-betting for mean estimation
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Communities recovered from binary activity when T ≫ N
Community detection for binary graphical models in high dimension
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Book unifies proofs for conformal prediction guarantees
Theoretical Foundations of Conformal Prediction
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Formula identifies causal effects from remote sensing by merging experiment and data
Program Evaluation with Remotely Sensed Outcomes
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Wasserstein depth ranks distributions by centrality
Wasserstein Spatial Depth
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Cross-fitting with out-of-sample losses fixes changepoint detection in complex models
Changepoint Detection in Complex Models: Cross-Fitting Is Needed
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Matching estimators obey non-normalized CLT with explicit variance
Limit theorems of matching estimators with a fixed number of matches
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Bayesian latent knockoffs control FDR at any level
Bayesian Controlled FDR Variable Selection via Parameter-Expanded Latent Knockoffs
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Sp-GD recovers max-affine parameters from O(s log(d/s)) samples
Sparse Max-Affine Regression
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kNN Laplacians reach O(N^{-2/(d+6)}) convergence on manifolds
Improved convergence rate of kNN graph Laplacians: differentiable self-tuned affinity
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Layered clusters improve tail exponent estimates with missing data
Layered Hill estimator for extreme data in clusters
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Batch variance update beats Ross method unless batch size is one
Extending Sheldon M. Ross's Method for Efficient Large-Scale Variance Computation
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Undetectable corruption radius is twice Gaussian width for symmetric sets
Can we spot a fake?
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Any conditional independence test yields a conditional two-sample test
General Frameworks for Conditional Two-Sample Testing
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Non-central matrix ratio distribution derived
On non-central distribution of the matrix ratio
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Minimax mean estimation error under arbitrary missingness decomposes into MCAR quantiles…
Estimation beyond Missing (Completely) at Random
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Staleness factor model removes bias from high-frequency co-volatility estimates
Staleness Factors and Volatility Estimation at High Frequencies