Author

J. Spall

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Preprint Oct 2026

High-Dimensional Regularization of the Spatial Sign Covariance Matrix for Robust Shape Estimation

Covariance estimation is a key component of many applications in system identification and data-driven control. Although heavy-tailed distributions may lack a covariance matrix to estimate, the shape matrix provides a well-defined, scale-free generalization for the broad family of elliptical distributions. In this sett...

Jonas Elmerraji, J. Spall, Mateo Díaz · 0 citations

Preprint Aug 2026

Zeroth-Order Langevin Monte Carlo via SPSA under Noisy Function Measurements

In sampling problems, gradient-based schemes such as Langevin Monte Carlo (LMC) mix faster than non-gradient-based methods, but their applicability is limited by access to the gradient of the target log-density. In practice, gradients are often unavailable and function evaluations are noisy, e.g., stochastic simulators...

Hongbo Li, J. Spall · 0 citations