X He, R Hu, YP Fang - Applicable Analysis, 2023 - Taylor & Francis
We propose an inertial primal-dual dynamic with damping and scaling coefficients, which involves inertial terms both for primal and dual variables, for a linearly constrained convex …
L Guo, I Korovin, S Gorbachev, X Shi, N Gorbacheva… - Neural Networks, 2024 - Elsevier
This paper considers a class of multi-agent distributed convex optimization with a common set of constraints and provides several continuous-time neurodynamic approaches. In …
X He, R Hu, Y Fang - Applied Mathematics & Optimization, 2024 - Springer
The class of convex–concave bilinear saddle point problems encompasses many important convex optimization models arising in a wide array of applications. The most of existing …
Z Jiang, D Wang, X Liu - Optimization Letters, 2024 - Springer
We aim to solve the linearly constrained convex optimization problem whose objective function is the sum of a differentiable function and a non-differentiable function. We first …
H Luo - arXiv preprint arXiv:2407.20195, 2024 - arxiv.org
In this paper, based a novel primal-dual dynamical model with adaptive scaling parameters and Bregman divergences, we propose new accelerated primal-dual proximal gradient …
H Luo - arXiv preprint arXiv:2405.14098, 2024 - arxiv.org
We give a continuous perspective on the Inertial Corrected Primal-Dual Proximal Splitting (IC-PDPS) proposed by Valkonen ({\it SIAM J. Optim.}, 30 (2): 1391--1420, 2020) for solving …
We examine stability properties of primal-dual gradient flow dynamics for composite convex optimization problems with multiple, possibly nonsmooth, terms in the objective function …
In this paper, we propose in a Hilbertian setting a second-order time-continuous dynamic system with fast convergence guarantees to solve structured convex minimization problems …
X Sun, L Zheng, KL Teo - arXiv preprint arXiv:2408.06884, 2024 - arxiv.org
This paper deals with a Tikhonov regularized second-order plus first-order primal-dual dynamical system with time scaling for separable convex optimization problems with linear …