2 papers
stat.ML2026
Score-based Metropolis-Hastings for Fractional Langevin Algorithms
Ahmed Aloui, Junyi Liao, Ali Hasan +2
Sampling from heavy-tailed and multimodal distributions is challenging when neither the target density nor the proposal density can be evaluated, as in -stable Lévy-driven fract…
stat.ML2024
Limit Theorems for Stochastic Gradient Descent with Infinite Variance
Jose Blanchet, Aleksandar Mijatović, Wenhao Yang
Stochastic gradient descent is a classic algorithm that has gained great popularity especially in the last decades as the most common approach for training models in machine learni…