M. Berk Sahin

Variance-Reduced Zeroth-Order Langevin Dynamics for Non-Log-Concave Black-Box Sampling and Inverse Problems

Sampling from high-dimensional, non-log-concave distributions with unnormalized densities constitutes a fundamental challenge in machine learning, particularly when gradient information is inaccessible or computationally prohibitive. While Langevin dynamics provides a robust mechanism for gradient-b…