Zobrazeno 1 - 10
of 787
pro vyhledávání: '"Li Huaqing"'
Publikováno v:
Open Geosciences, Vol 14, Iss 1, Pp 813-823 (2022)
The response of beaches to typhoons has always been a hot topic at home and abroad. The study of beach changes during typhoons is helpful to deepen the understanding of beach evolution and is important for the coastal ecological environment. Based on
Externí odkaz:
https://doaj.org/article/df52db4eebe24579b27764ea003d5fb0
Privacy leakage and Byzantine failures are two adverse factors to the intelligent decision-making process of multi-agent systems (MASs). Considering the presence of these two issues, this paper targets the resolution of a class of nonconvex optimizat
Externí odkaz:
http://arxiv.org/abs/2409.18632
This paper considers a class of noncooperative games in which the feasible decision sets of all players are coupled together by a coupled inequality constraint. Adopting the variational inequality formulation of the game, we first introduce a new loc
Externí odkaz:
http://arxiv.org/abs/2402.03669
Publikováno v:
IEEE Transactions on Signal and Information Processing over Networks, 2024
Distributed optimization is manifesting great potential in multiple fields, e.g., machine learning, control, and resource allocation. Existing decentralized optimization algorithms require sharing explicit state information among the agents, which ra
Externí odkaz:
http://arxiv.org/abs/2308.08164
Publikováno v:
Engineering Applications of Artificial Intelligence 99 (2021) 104151
This paper studies optimization problems over multi-agent systems, in which all agents cooperatively minimize a global objective function expressed as a sum of local cost functions. Each agent in the systems uses only local computation and communicat
Externí odkaz:
http://arxiv.org/abs/2305.11469
Publikováno v:
IEEE Transactions on Network Science and Engineering, VOL. 10, NO. 2, 2023, PP. 934-950
Distributed stochastic optimization, arising in the crossing and integration of traditional stochastic optimization, distributed computing and storage, and network science, has advantages of high efficiency and a low per-iteration computational compl
Externí odkaz:
http://arxiv.org/abs/2305.09181
Decentralized stochastic gradient algorithms resolve efficiently large-scale finite-sum optimization problems when all agents over networks are reliable. However, most of these algorithms are not resilient to adverse conditions, such as malfunctionin
Externí odkaz:
http://arxiv.org/abs/2305.08051
In the intricate dance of multi-agent systems, achieving average consensus is not just vital--it is the backbone of their functionality. In conventional average consensus algorithms, all agents reach an agreement by individual calculations and sharin
Externí odkaz:
http://arxiv.org/abs/2304.08018