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1,205 records
- Strang splitting estimator for nonlinear multivariate stochastic differential equations with Pearson-type multiplicative noise
- HASOD: A Hybrid Adaptive Screening-Optimization Design for High-Dimensional Industrial Experiments
- Model Checking for Regressions Based on Weighted Residual Processes with Diverging Number of Predictors
- Theta-regularized Kriging: Modelling and Algorithms
- Structural interpretability in SVMs with truncated orthogonal polynomial kernels
- One-Shot Generative Flows: Existence and Obstructions
- Robust Low-Rank Tensor Completion based on M-product with Weighted Correlated Total Variation and Sparse Regularization
- Information-Geometric Decomposition of Generalization Error in Unsupervised Learning
- $p$-adic Linear Regression for Random Sampling with Digitwise Noise
- Adaptive Learning via Off-Model Training and Importance Sampling for Fully Non-Markovian Optimal Stochastic Control. Complete version
- Rare Event Analysis via Stochastic Optimal Control
- Identifiability of Potentially Degenerate Gaussian Mixture Models With Piecewise Affine Mixing
- Addressing Confounding by Indication Through (Un)Measured Centre Characteristics in Learn-As-you-GO(LAGO) Trials
- Cyclic fractional Gaussian noise: time and frequency domain properties
- Cost-optimal Sequential Testing via Doubly Robust Q-learning
- Extended One-Liners for the Beta, Gamma, and Dirichlet Distributions with Shape Parameters Below One
- ADD for Multi-Bit Image Watermarking
- NetworkNet: A Deep Neural Network Approach for Random Networks with Sparse Nodal Attributes and Complex Nodal Heterogeneity
- Inferring Change Points in Regression via Sample Weighting
- On the continuum limit of t-SNE for data visualization
- Reliability estimation in dependent stress-strength model with Clayton copula and modified Weibull margins
- Tail-Aware Information-Theoretic Bounds for LLM Alignment under Heavy-Tailed Rewards
- Toward Exact Convergence in Byzantine-Robust Decentralized Learning: A Statistical Identification Approach
- Uncertainty Quantification for Noisy Low-tubal-rank Tensor Completion
- Online Quantile Regression for Nonparametric Additive Models
- Identifying Causal Effects Using a Single Proxy Variable
- Partial correlation networks of Gaussian processes
- On the Unique Recovery of Transport Maps and Vector Fields from Finite Measure-Valued Data
- The Condition-Number Principle for Prototype Clustering
- Order-Optimal Sequential 1-Bit Mean Estimation in General Tail Regimes
- Intensity Dot Product Graphs
- A Transport Geometry of Benign Overfitting
- Bathymetry Reconstruction by Bayesian Inference
- Simulation Based Inference of a Simple Neural Network Structure
- Amortized Filtering and Smoothing with Conditional Normalizing Flows
- Gaussian Approximation for Asynchronous Q-learning
- Conformal Prediction with Time-Series Data via Sequential Conformalized Density Regions
- Poisson-response Tensor-on-Tensor Regression and Applications
- Marginal Persistence and Dynamic Copula Dependence in Sovereign Rating Migration Counts: A Discrete Interval-Likelihood MAGMAR Analysis
- Hierarchical Contrastive Learning for Multimodal Data
- Sufficient conditions for proper posteriors in fully-Bayesian Functional PCA
- Generalization error bounds for two-layer neural networks with Lipschitz loss function
- NS-RGS: Newton-Schulz based Riemannian gradient method for orthogonal group synchronization
- Noisy Nonreciprocal Pairwise Comparisons: Scale Variation, Noise Calibration, and Admissible Ranking Regions
- Hypothesis Testing for Penalized Estimating Equations with Cross-Fitted Covariance Calibration
- On Data Thinning for Model Validation in Small Area Estimation
- Sharp asymptotic theory for Q-learning with LDTZ learning rate and its generalization
- Efficient estimation of relative risk, odds ratio and their logarithms for rare events
- State estimations and noise identifications with intermittent corrupted observations via Bayesian variational inference
- Identification and Inference in Nonlinear Dynamic Network Models