Nonasymptotic estimates for Stochastic Gradient Langevin Dynamics under local conditions in nonconvex optimization. - Ying Zhang 037; Ömer Deniz Akyildiz; Theo Damoulas; Sotirios Sabanis (CoRR, 2019)

On explicit order 1.5 approximations with varying coefficients: The case of super-linear diffusion coefficients. - Sotirios Sabanis; Ying Zhang 037 (J. Complex., 2019)

Non-asymptotic estimates for TUSLA algorithm for non-convex learning with applications to neural networks with ReLU activation function. - Dong-Young Lim; Ariel Neufeld; Sotirios Sabanis; Ying Zhang 037 (CoRR, 2021)

On Stochastic Gradient Langevin Dynamics with Dependent Data Streams: The Fully Nonconvex Case. - Ngoc Huy Chau; Éric Moulines; Miklós Rásonyi; Sotirios Sabanis; Ying Zhang 037 (SIAM J. Math. Data Sci., 2021)

Non-asymptotic convergence bounds for modified tamed unadjusted Langevin algorithm in non-convex setting. - Ariel Neufeld; Matthew Ng Cheng En; Ying Zhang 037 (CoRR, 2022)

Langevin dynamics based algorithm e-THεO POULA for stochastic optimization problems with discontinuous stochastic gradient. - Dong-Young Lim; Ariel Neufeld; Sotirios Sabanis; Ying Zhang 037 (CoRR, 2022)

On diffusion-based generative models and their error bounds: The log-concave case with full convergence estimates. - Stefano Bruno; Ying Zhang 037; Dongyoung Lim; Ömer Deniz Akyildiz; Sotirios Sabanis (Trans. Mach. Learn. Res., 2025)

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients. - Iosif Lytras; Sotirios Sabanis; Ying Zhang 037 (CoRR, 2025)