AI & Machine Learning · Computer Science & AI
Machine Learning (Statistics)
The newest papers in Machine Learning (Statistics) that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
1,749 papers, from 4 September 2026 to 5 November 2026: 1,749 arXiv preprints.
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Newest papers, page 25
Learned Control Variates for Rare Grid-Outage Estimation at Electric Vehicle Charging Stations
Public charging of electric vehicles (EVs) adds a large and synchronized load to the distribution feeders.Diffusion Score Estimation with Shallow Neural Networks: Regularity, Approximation, and Finite-Sample Rates
We study the sample complexity of estimating Ornstein--Uhlenbeck diffusion scores in $\mathbb R^d$ using denoising score matching (DSM) with finite-width shallow ReLU networks, and its implications…Solving the Ho--Nguyen Conjecture for Gaussian Mixtures: Applications to Mixtures of Experts
Over-fitted Gaussian mixtures can contain many parameter configurations with nearly the same density, making the order of density cancellation central to their parameter-learning rates.VampPrior Unleashed
Deep latent variable models (DLVMs) underpin many modern analysis pipelines, for example in single-cell genomics, yet their prior distributions have received markedly little attention.A plug-in estimator of the non-iterative conditional expectation g-formula using long short-term memory models
The non-iterative conditional expectation (NICE) plug-in estimator of the g-formula can be used to estimate the causal effects of sustained treatment strategies, even in the presence of…Communication Complexity of Universal Features
Motivated by the notion of features from machine learning, we study the complexity of representing data that allows for evaluation with a given family of functions.Robust Direct Preference Optimization under Preference Label-Flip Attacks
Direct Preference Optimization (DPO) is widely used for offline Reinforcement Learning from Human Feedback.Dimension-free comparison inequalities between $f$-divergences for Gaussian location mixtures
We establish dimension-free comparison inequalities between the Kullback-Leibler (KL) and $χ^2$-divergences and the squared Hellinger distance for Gaussian location mixtures with compactly supported…Decision-Target Reversal under Informative Label Missingness
Informative label missingness can improve classification efficiency because the pattern of label availability may itself contain information about the discriminant structure.A Distribution-Free Separation Between Learned and Fixed Features
The success of neural networks is largely attributed to their ability to learn useful representations from training data.DR-Learners for Generalizing CATEs from a Randomized Controlled Trial
Randomized clinical trials are essential for evaluating interventions, yet average treatment effects can obscure treatment effect heterogeneity, making conditional average treatment effects (CATEs)…Reinforcement learning on the EPRI AI-ccelerating Unit Commitment benchmark: diagnosing over-commitment and guiding MILP with learned policies
Reinforcement learning (RL) is increasingly proposed as a fast solver for unit commitment (UC), but standalone agents remain far more expensive than mixed-integer linear programming (MILP).Divergence based Ranked Preference Alignment for LLMs
Alignment of large language models typically relies on pairwise preference feedback, though ranked feedback can capture more comprehensive information across multiple responses within a single…Quadratic Sample Complexity for Strictly Replicable Realizable Learning with Unknown Marginals
Under the quantifier $\exists A\,\forall D$, where the realizable distribution and its marginal are unknown, we determine the finite-class sample-complexity exponent for strict replicability: two…Uniform convergence at optimal rate and scale
Uniform convergence asks how many random samples suffice for empirical averages to approximate expectations simultaneously over an entire class of functions.The Certification Exponent: Instance-Optimal Sequential Certification of Policy Improvement from History Dependent Logs
Before a new policy replaces a deployed one, we often want a certificate, computed from logged episodes, that it is better.Private Evaluation of High-Dimensional Functions
We study differentially private black-box evaluation of arbitrary high-dimensional functions.Denoising Implicit Variational Inference
Semi-implicit variational inference (SIVI) expands the representational capacity of variational families, but optimizing the Evidence Lower Bound (ELBO) remains challenging because the marginal…Accelerating Finite-Sum Bilevel Optimization with Fully First-Order Oracles
We study nonconvex--strongly-convex bilevel optimization with finite-sum objectives and fully first-order oracles.Conditional Weight of Evidence for Gradient-Boosted Credit Models: Estimation, Additivity and Its Relation to Adverse Action Reasons
Traditional weight of evidence assigns a credit characteristic a value based on its association with default across a population.