Sotirios Sabanis | DeepAI

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∙ 03/23/2023

Interacting Particle Langevin Algorithm for Maximum Marginal Likelihood Estimation

We study a class of interacting particle systems for implementing a marg...

0 Ö. Deniz Akyildiz, et al. ∙

∙ 01/19/2023

Kinetic Langevin MCMC Sampling Without Gradient Lipschitz Continuity – the Strongly Convex Case

In this article we consider sampling from log concave distributions in H...

0 Tim Johnston, et al. ∙

∙ 10/24/2022

Langevin dynamics based algorithm e-THεO POULA for stochastic optimization problems with discontinuous stochastic gradient

We introduce a new Langevin dynamics based algorithm, called e-THεO POUL...

0 Dong-Young Lim, et al. ∙

∙ 12/31/2021

A Strongly Monotonic Polygonal Euler Scheme

Rate of convergence results are presented for a new class of explicit Eu...

0 Tim Johnston, et al. ∙

∙ 10/21/2021

Statistical Finite Elements via Langevin Dynamics

The recent statistical finite element method (statFEM) provides a cohere...

0 Ömer Deniz Akyıldız, et al. ∙

∙ 07/19/2021

Non-asymptotic estimates for TUSLA algorithm for non-convex learning with applications to neural networks with ReLU activation function

We consider non-convex stochastic optimization problems where the object...

0 Dong-Young Lim, et al. ∙

∙ 05/28/2021

Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks

We present a new class of adaptive stochastic optimization algorithms, w...

0 Dong-Young Lim, et al. ∙

∙ 07/02/2020

A fully data-driven approach to minimizing CVaR for portfolio of assets via SGLD with discontinuous updating

A new approach in stochastic optimization via the use of stochastic grad...

0 Sotirios Sabanis, et al. ∙

∙ 06/25/2020

Taming neural networks with TUSLA: Non-convex learning via adaptive stochastic gradient Langevin algorithms

Artificial neural networks (ANNs) are typically highly nonlinear systems...

0 Attila Lovas, et al. ∙

∙ 02/13/2020

Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization

We provide a nonasymptotic analysis of the convergence of the stochastic...

0 Ömer Deniz Akyıldız, et al. ∙

∙ 10/04/2019

Nonasymptotic estimates for Stochastic Gradient Langevin Dynamics under local conditions in nonconvex optimization

Within the context of empirical risk minimization, see Raginsky, Rakhlin...

0 Ying Zhang, et al. ∙

∙ 05/30/2019

On stochastic gradient Langevin dynamics with dependent data streams: the fully non-convex case

We consider the problem of sampling from a target distribution which is ...

0 Ngoc Huy Chau, et al. ∙

∙ 08/02/2018

Higher Order Langevin Monte Carlo Algorithm

A new (unadjusted) Langevin Monte Carlo (LMC) algorithm with improved ra...

0 Sotirios Sabanis, et al. ∙

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