[HTML][HTML] A distributed proximal gradient method with time-varying delays for solving additive convex optimizations
We consider the problem of minimizing a finite sum of differentiable and nondifferentiable
convex functions in the setting of finite-dimensional Euclidean space. We propose and …
convex functions in the setting of finite-dimensional Euclidean space. We propose and …
An asynchronous subgradient-proximal method for solving additive convex optimization problems
In this paper, we consider additive convex optimization problems in which the objective
function is the sum of a large number of convex nondifferentiable cost functions. We assume …
function is the sum of a large number of convex nondifferentiable cost functions. We assume …
[HTML][HTML] A delayed subgradient method for nonsmooth convex-concave min–max optimization problems
T Arunrat, N Nimana - Results in Control and Optimization, 2023 - Elsevier
In this paper, we aim to solve a convex-concave min–max optimization problem, where the
convex-concave coupling function is nonsmooth in both variables. We propose a simple …
convex-concave coupling function is nonsmooth in both variables. We propose a simple …
Inertial proximal incremental aggregated gradient method with linear convergence guarantees
X Zhang, W Peng, H Zhang - Mathematical Methods of Operations …, 2022 - Springer
In this paper, we propose an inertial version of the Proximal Incremental Aggregated
Gradient (abbreviated by iPIAG) method for minimizing the sum of smooth convex …
Gradient (abbreviated by iPIAG) method for minimizing the sum of smooth convex …
[HTML][HTML] First-Order Algorithms for Communication Efficient Distributed Learning
S Khirirat - 2022 - diva-portal.org
Innovations in numerical optimization, statistics and high performance computing have
enabled tremendous advances in machine learning algorithms, fuelling applications from …
enabled tremendous advances in machine learning algorithms, fuelling applications from …