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- Optimizing Sparse Boolean Rule Networks using Mixed Integer Linear Programming
- Predicting future insurance markets: Simulation of technology adoption paths with a Bayesian Bass model
- Discrete p-Fold Directional Models for Binned Orientation Data with Applications to Sand-Grain Orientations and Urban Street Networks
- A Large-Dimensional Analysis of Least-Squares Federated Learning via Generalized Total Variation Minimization
- Testing for Peer Effects in Heteroskedastic Fixed-Effects Panels
- Outperforming 1000 Euclidean Layers With Hyperbolic Goal-Conditioned RL
- Convergence Rates of Gaussian Process Thompson Sampling for Efficient Global Optimization
- Improved Forecasting for Multivariate Time Series using GNAR models with General Inverse Distance Weights
- Interactive and Robust PCA Graphics with FSDA in MATLAB
- Neural Wasserstein Splines: Representation-Invariant Second-Order Priors for Trajectory Inference
- Principal Component Analysis for Zero-Inflated Probability Measures via Lorenz Curves
- Text-Informed Training Data Filtering for Enhanced Virtual Flow Meter Performance
- Calibration and Risk-Budgeted Decisions with System One Models
- Efficient contextual partial monitoring with general function approximation
- Generalized Odds for Ordinal Outcomes: A Causal Inference Framework Adjusting for Covariates
- Annealed Lévy Diffusion via Gaussian Surrogate Reverse Dynamics
- Function-Space Temporal Self-Distillation for Policy Optimization
- SULA: Robust Langevin Sampling via Drift-Diffusion Saturation
- On Global Joint Lower Bounds in Zeroth-Order Nonconvex Optimization
- Risk-Controlled DFT Selection for Machine-Learned Interatomic Potentials
- Projected Wasserstein-Fisher-Rao Flows for Hawkes Background-Intensity Estimation
- Noisy-Label Calibration with Multiple Unreliable Labels
- State-Matched Sequence Conformal Prediction
- Common Signals, Spurious Cross-Excitation, and Identification in Multivariate Hawkes Processes
- Longitudinal Brain Aging in Covariance Space: Temporally Calibrated Bayesian Inference for Adaptive Covariance Operators