1,205 records
- A unified approach for estimation of unnormalized models via Stein operators
- Differentially Private Synthetic Data via Generalized Moment Matching
- Bridge change-of-measure for propagator estimation of diffusions
- Beyond exponential tilting: sharp asymptotics and improved importance sampling for rare events
- Geometry-informed importance sampling for rare events
- Annealed correlation and quenched noise sensitivity in biased deep neural networks
- Nonparametric In-Context Learning and Inference via Measure-Indexed Kernel Ridge Regression
- Likelihood-Based Confidence Curves for Bounded Parameters
- Confessions of a Masked MDP
- Borrowing Strength Across Stores: Transfer Learning for Choice-Based Revenue Management
- Anytime-Valid Inference in Linear Models with Clustered Outcomes: Exact Multivariate Tests and Cluster-Robust Confidence Sequences
- Corrected Block Sparse Spectral Optimization: Exact Models, Finite Identification, and Local Dynamics
- Gaussian Approximation of Besov Functions for Logistic Classification on Manifolds
- The Geometry of Informativeness: A Bregman-Centroid Diagnostic for Partial Pooling in Multisite Trials
- Information-Geometric Blind Spots of Conformal Test Martingales
- Testing Treatment Effect Heterogeneity with Functional Outcomes
- A general recipe for data-adaptive anytime-valid envelopes for iterative algorithms
- Parametric Resonance in Primal-Dual Learning for Slowly Non-Stationary Constrained MDPs
- PICKLES: Covariance-Preconditioned Kinetic Langevin Ensemble Sampler
- Pathwise Shrinkage and Probabilistic Calibration of the Multiplicative Half-Cauchy Process
- Reconstructing constant point heat sources from few temperature sensors: sparse selection and spatial resolution
- Dimension-Free PAC-Bayes Generalization for Deep Neural Networks via Dirichlet Processes
- A perturbation theory for Feynman-Kac models and their particle interpretations
- Optimal approximation of smooth functions by ReLU neural networks
- Negative-binomial ensemble filtering for discrete-time Hawkes network reconstruction
- On Inherent Privacy of Posterior Sampling: A Unified Rényi-Divergence Framework
- Model-Induced Hazard Geometry and Functional Representations in Survival Analysis
- On the Optimisation Landscape of Overparameterised Weighted MMD
- Minimax estimation of the pseudo-spectral gap of continuous Markov chains, with applications to empirical concentration bounds
- MCMC Can See Can't See
- A polylogarithmic bound for list replicability
- Stochastic Gradient Descent: A Nonlinear Time Series Perspective
- Two-Stage Score Estimation for Group-Specific Diffusion Models
- Acceleration and its Limits in Gaussian Variational Inference
- Risk-Averse Inference-Time Diffusion Model Alignment with Finite-Sample Guarantees
- textGrain watermarking is harder to detect: can sum-tests still do it optimally?
- How to Train Your Intercept: A Comparison of Intercept Update Strategies in Coordinate Descent
- Sparse-group Convoluted Smoothed Quantile Regression in High Dimension
- Multilevel Main Effects Matrix Factor Model
- Rapid Mixing of Stereographic MCMC for Heavy-Tailed Sampling
- Wong--Zakai Convergence and FNO Learning for Stochastic Volterra Equations
- Conformalized Physics-Informed Weak Regression for Parameter Estimation in Epidemic Models
- Limit Theory for Online Expectile Estimation under Short and Long Range Dependence
- Distributional Regression for Arbitrary Response Variables Using ReLU Neural Networks
- Exploration strategies for Gaussian process bandit optimization with inference regret guarantees
- Adaptive Cauchy inference from invariant information
- Feature Normalization under Finite Training Budgets
- Overlap, Not Moments: Finite-Sample Theory for Bridge Sampling
- Moment-Calibrated Conformal Prediction with Side Information
- When do explicit penalties improve flow matching?