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- Second-Order Least Squares Method for Statistical Inference in Linear Models with Asymmetric Errors
- HALO: Hierarchical Evidence Selection and Reinforcement Learning for Allocating Budgeted Label Optimization from Longitudinal Clinical Records
- Riemannian Newton Methods with Statistical Inference
- Bootstrap Inference for Riemannian Optimization Problems
- A Bayesian Magnitude-Composition Model for Tree-Size Distributions and Stand-Tables
- Differential Privacy for Generalized Entropy Indices of Income Inequality
- Finite-Sample Calibration and Power Benchmarks in Two-Sample Random-Integration Tests
- Power-optimal allocation in multi-arm cluster randomized trials
- Tight Stochastic Sequential Covers for General VC Classes with Unknown i.i.d. Features
- Sampling Design and Confidence Tubes for Integral Curves on Riemannian Manifolds
- Model-Based Learning of Latent Euclidean Embedding from Relational Data
- Causal Record Linkage
- Pricing Today, Shaping Tomorrow: Contextual Dynamic Pricing in Purchase-Driven Evolving Systems
- Nonnegativity Shapes Predictive Uncertainty: Complementary Model Fits and Quantile Construction
- Representative Learning for Distributed Support Vector Machines
- Movement based social interactions with label uncertainty
- Artificial Intelligence in Pharmaceutical Development: Building Rigorous, Decision-Ready Evidence
- Efficient Causal Survival Inference under Limited Surrogate Monitoring
- Characterizing Estimator-Regime Transitions in Adaptive Enrichment Trials
- Robust Inference for Spiked Eigenspace under Elliptical Distributions
- Time-Specific Multinomial Logistic Regression for Competing Risks
- Where Causal Discovery Breaks on Real Data: Measuring the Assumptions One Property at a Time
- Power-Optimal Risk Control via Standardized Margin Calibration
- Guide to Teaching with Data in Statistics and Data Science Classrooms
- Penalized Likelihood Inference in Highly Multivariate Sparse Spectral Graphical Gaussian Processes