Sotirios Sabanis

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 19

Top Topics

Asymptotic Analysis

Stochastic Gradient

Nearest Neighbor Classifier

Top Venues

SIAM J. Math. Data Sci.

SIAM/ASA J. Uncertain. Quantification

Publications

Tim Johnston, Sotirios Sabanis
A strongly monotonic polygonal Euler scheme. J. Complex. 80 (2024)
Tim Johnston, Iosif Lytras, Sotirios Sabanis
Kinetic Langevin MCMC sampling without gradient Lipschitz continuity - the strongly convex case. J. Complex. 85 (2024)
Attila Lovas, Iosif Lytras, Miklós Rásonyi, Sotirios Sabanis
Taming Neural Networks with TUSLA: Nonconvex Learning via Adaptive Stochastic Gradient Langevin Algorithms. SIAM J. Math. Data Sci. 5 (2) (2023)
Stefano Bruno, Ying Zhang, Dong-Young Lim, Ömer Deniz Akyildiz, Sotirios Sabanis
On diffusion-based generative models and their error bounds: The log-concave case with full convergence estimates. CoRR (2023)
M. Barkhagen, Sergio García, Jacek Gondzio, Jörg Kalcsics, J. Kroeske, Sotirios Sabanis, A. Staal
Optimising portfolio diversification and dimensionality. J. Glob. Optim. 85 (1) (2023)
Iosif Lytras, Sotirios Sabanis
Taming under isoperimetry. CoRR (2023)
Tim Johnston, Iosif Lytras, Sotirios Sabanis
Kinetic Langevin MCMC Sampling Without Gradient Lipschitz Continuity - the Strongly Convex Case. CoRR (2023)
Ömer Deniz Akyildiz, Connor Duffin, Sotirios Sabanis, Mark Girolami
Statistical Finite Elements via Langevin Dynamics. SIAM/ASA J. Uncertain. Quantification 10 (4) (2022)
Dong-Young Lim, Ariel Neufeld, Sotirios Sabanis, Ying Zhang
Langevin dynamics based algorithm e-THεO POULA for stochastic optimization problems with discontinuous stochastic gradient. CoRR (2022)
Dong-Young Lim, Ariel Neufeld, Sotirios Sabanis, Ying Zhang
Non-asymptotic estimates for TUSLA algorithm for non-convex learning with applications to neural networks with ReLU activation function. CoRR (2021)
Ömer Deniz Akyildiz, Connor Duffin, Sotirios Sabanis, Mark Girolami
Statistical Finite Elements via Langevin Dynamics. CoRR (2021)
Ngoc Huy Chau, Éric Moulines, Miklós Rásonyi, Sotirios Sabanis, Ying Zhang
On Stochastic Gradient Langevin Dynamics with Dependent Data Streams: The Fully Nonconvex Case. SIAM J. Math. Data Sci. 3 (3) (2021)
Dong-Young Lim, Sotirios Sabanis
Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks. CoRR (2021)
Tim Johnston, Sotirios Sabanis
A Strongly Monotonic Polygonal Euler Scheme. CoRR (2021)
Attila Lovas, Iosif Lytras, Miklós Rásonyi, Sotirios Sabanis
Taming neural networks with TUSLA: Non-convex learning via adaptive stochastic gradient Langevin algorithms. CoRR (2020)
Ying Zhang, Ömer Deniz Akyildiz, Theo Damoulas, Sotirios Sabanis
Nonasymptotic estimates for Stochastic Gradient Langevin Dynamics under local conditions in nonconvex optimization. CoRR (2019)
Sotirios Sabanis, Ying Zhang
On explicit order 1.5 approximations with varying coefficients: The case of super-linear diffusion coefficients. J. Complex. 50 (2019)
László Gerencsér, Balázs Csanád Csáji, Sotirios Sabanis
Asymptotic Analysis of the LMS Algorithm with Momentum. CDC (2018)
Konstantinos Dareiotis, Chaman Kumar, Sotirios Sabanis
On Tamed Euler Approximations of SDEs Driven by Lévy Noise with Applications to Delay Equations. SIAM J. Numer. Anal. 54 (3) (2016)