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1,244 records
- Reduced-Rank Autoregressive Models for Matrix Time Series
- Adaptive Random Matrices in Gaussian Bandits: Spectral Universality and Selection-Induced Outliers
- The Critical Line Algorithm and the Constrained LASSO: One Curve, Two Literatures
- Statistical Gains from Looped Estimation under Parameter Budgets
- Grouped Semi-Supervised Estimation of Two-Sample Functionals via Single-Index Conditional Imputation
- SuperPCA: subspace analysis and an efficient algorithm for high-dimensional PCA
- Empirical Bayes prepivoting under group invariance: false discovery rate control and moderated t-tests
- Stochastic Inertial Krasnosel'skii-Mann Iteration Achieves Near-Optimal Sample Complexity
- Doubly robust target inference for generalized linear regression with completely missing covariates
- Quantifying Long-Range Dependence in Object-Valued Time Series
- Adversarially Robust PAC Learning with Optimal VC Rates
- Variational objectives for amortized Bayesian inference in inverse problems: The role of posterior conditioning
- Closed forms and open obstructions: the sample variance of three observations
- Penalized Nonreversible Langevin for Constrained Sampling
- PICPIs: Prediction-Interval-Conditional Prediction Intervals
- SCOPE and REACH with almost-surely finite stopping times
- Streaming PCA: averaging from a geometric perspective
- Toscani-Fourier Distance on Probability Measures: Wasserstein Control, Topological Equivalence on Model Classes, and Duality
- Conformal Robustness in Prediction-Driven Decision-Making
- Bayesian Deck-of-cards-based Ordinal Regression with Sequential Preference Elicitation
- FREESIA: Covariance-Aware Posterior Transport for Expressive and Scalable Data Assimilation
- A Partial Fay-Herriot model for Small Area Estimation: Estimating district-level consumption in Mozambique
- Optimal study interior partitioning (OSIP): An optimization approach to observational study design under fine balance constraints
- Consistency of Optimal Matching-based Clustering for Mixtures of Markov Chains
- Locally Private Inference for Riemannian Stochastic Optimization
- Next-token functional estimation
- Oracle high-dimensional $M$-estimation using smooth reparameterization for sparsity
- Federated multiple testing with quantized p-values under family-wise error control
- Multi-Absorbing Phase-Type Distributions for Right-Censored Competing Risks Data
- Parameter Estimation for the Mixed Fractional Merton Jump Diffusion Model with EM Algorithm
- Exponential Smoothing for Time Series of Random Objects
- Conditional Independence Testing in Time Series
- Aggregated Posterior Predictive Checks for Generative Modeling
- A Smoothed Discrepancy Principle for Random Feature Methods and Neural Networks
- Triply-Scalable Equivariant Gaussian Process Modeling
- Taylor Diagram and Wasserstein Distance for Model Evaluation
- Drift Inference for Unit-Root Galton-Watson Processes with Immigration
- Preservation of Log-Concavity and Convergence of Wasserstein-Fisher-Rao Gradient Flows
- A General Kernel Framework for Non-CND Distance Measures Using |D|-Dimensional Sparse Landmark Embeddings
- Laplacian U-Processes for Multiple Change-Point Detection in Dependent Text Networks: An Application to Historical Chinese Articles
- Optimal Scaling of Langevin Proposals with Generalized Acceptance Rules
- Conformal Policy Learning with Distribution-Free Safety Guarantees
- Sharp margin-based generalization bounds for realizable SVM
- Generalized DCCQ: From Binary Quotients to Multinomial Simplex Geometry and Critical-Strip Coordinates
- Steady-State Convergence of Stochastic Approximation
- Stability-Constrained Approximation in Spline KANs: Exact Layer Balancing and Budget-Compatible Saturation
- Bootstrap-Calibrated Spectral Divergence Tests for Online Detection of Covariance Matrix Changes
- Evaluation of optimisation and Bayesian inference methods for reaction rates in atmospheric chemical mechanisms
- Spectral Design of Random-Duration Switchbacks
- Resolution-Independent Analysis of Encoder--Decoder Operator Learning via Limiting Kernels