Probability & Statistics · Mathematics & Statistics
Statistics Theory
The newest papers in Statistics Theory that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
321 papers, from 31 August 2026 to 4 November 2026: 287 arXiv preprints and 34 OpenAlex records.
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Newest papers, page 14
Efficient computation of mixture confidence sequences in generalized linear models
Classical confidence intervals, when repeatedly obtained on accumulating data at different sample sizes, produce contradictory inferences with high probability.On the Identifiability of Mixed Ordinal and Exponential Family Causal DAGs under Linear Parametric Models
The problem of identifiability in linear parametric models (LPMs) whose nodes follow either an ordered logit model or a regular one-parameter exponential family is evaluated.Double descent is the principle of least action
The test error of a model plotted against its number of parameters $d$ falls, peaks when the model can just fit the training data, and falls again, exhibiting the double descent phenomenon.Stable Policy Learning
In evidence-based policymaking, typically one experimental sample is observed, then a learned policy recommendation is implemented at scale.Sparse Priors for Efficient Distribution Learning
Despite the widespread use and success of generative AI techniques today, theoretical guarantees on learning a distribution supported in $d$ dimensions from $n$ samples degrade as $O(n^{-1/Θ(d)})$…Characterizing Heterogeneous Rates in Finite Mixture Estimation via Partial Optimal Transport
Parameter estimation in finite mixture models can exhibit highly heterogeneous convergence behavior: locally isolated components may be estimated substantially faster than groups of competing…Conformal Policy Learning with Distribution-Free Safety Guarantees
Policy learning aims to determine who should be treated based on individual characteristics.Coupled Calibration and Learning: Mitigating Teacher Bias in LLM Distillation without Target-Domain Reward Feedback
Large language model (LLM) distillation aims to transfer the capabilities of a powerful teacher to a smaller student.Fenchel-Young Duality Gaps: Certified Early Stopping for Regularized Inverse Problems
We study computable error bounds and certified early stopping for regularized inverse problems, where a data-fidelity term is traded against a regularizer.Sharp margin-based generalization bounds for realizable SVM
Let the exact homogeneous hard-margin support vector machine be trained on \(m\) independent observations from a Borel probability law on a real Hilbert space.Retrieval-Guided Fine-Tuning as Noisy Estimation: Risk bounds and Architectural Analysis
Retrieval-Guided Fine-Tuning (RAG-FT) incorporates retrieved data directly into the training objective, but the statistical consequences of noisy retrieval during training remain theoretically…PDE-constrained inverse problems at the $\sqrt{n}$ rate via debiased physics-informed neural networks
We study the problem of estimating unknown parameters in PDE-constrained inverse problems from noisy observations, where the PDE solution is approximated using Physics-Informed Neural Networks…Inference for Newton Methods with Accelerated Sketch-and-Project via Random Scaling
We study an online sketched Newton method that approximates the Newton direction at each step via a state-of-the-art sketching solver, called the generalized accelerated sketch-and-project solver…Exact Community Recovery in Bipartite Networks
Community detection in bipartite networks is a fundamental problem in modern data analysis, with applications in recommendation systems, biological networks, and social network analysis.Tight Sampling Complexity with stochastic gradient oracles in Fixed Dimensions
We investigate the stochastic-gradient query complexity of sampling smooth strongly log-concave distributions in any fixed Euclidean dimension.Assumption-Lean Inference for Spectral Differential Network Analysis of High-Dimensional Time Series
Network analysis for multivariate time series is popular in many fields, from neuroscience to seismology.Closed-form estimation of the exponential scale under two-sided informative random censorship
We estimate the scale of an exponential lifetime from observations censored randomly from both sides, under an informative model in which each censoring law is a power of the lifetime survival…Identifiability of Nonnegative Tensor Decompositions via Positive Scattering
Identifiability of tensor decompositions is often established through linear-algebraic conditions on the factor families.Near-Gaussian counterexamples to the Ball-Nayar-Tkocz entropy concavity conjecture
The Ball-Nayar-Tkocz conjecture asserts that, for independent real random variables $X,Y$ with a common log-concave density, the function $t\mapsto h(\sqrt tX+\sqrt{1-t}Y)$ is concave on $[0,1]$.Signal Correlation, IC, and PnL Dependence
Signal correlation and PnL correlation are correlations over different index sets - across assets at each date versus across dates for scalar payoffs - and practitioners often treat the first as a…