Zobrazeno 1 - 10
of 193 547
pro vyhledávání: '"Local information"'
Autor:
Huang, Yuqin1 (AUTHOR), Li, Feng2 (AUTHOR), Li, Tong3 (AUTHOR) litong@xmu.edu.cn, Lin, Tse‐Chun4,5 (AUTHOR)
Publikováno v:
Contemporary Accounting Research. Jun2024, Vol. 41 Issue 2, p1089-1119. 31p.
In this paper, we explore how to optimize task allocation for robot swarms in dynamic environments, emphasizing the necessity of formulating robust, flexible, and scalable strategies for robot cooperation. We introduce a novel framework using a decen
Externí odkaz:
http://arxiv.org/abs/2411.19526
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1-18, 2024, Art no. 4709118
Remote sensing cross-modal text-image retrieval (RSCTIR) has gained attention for its utility in information mining. However, challenges remain in effectively integrating global and local information due to variations in remote sensing imagery and en
Externí odkaz:
http://arxiv.org/abs/2411.14704
Autor:
Cho, Young Sul
When a link is occupied to restrict the growth of large clusters using the size information of a finite number of finite clusters, so-called local information, an abrupt but continuous transition is exhibited. We report here that a hybrid transition
Externí odkaz:
http://arxiv.org/abs/2408.08572
In our previous works, we defined Local Information Privacy (LIP) as a context-aware privacy notion and presented the corresponding privacy-preserving mechanism. Then we claim that the mechanism satisfies epsilon-LIP for any epsilon>0 for arbitrary P
Externí odkaz:
http://arxiv.org/abs/2410.12309
Autor:
Cai, Xiumei1 (AUTHOR), Yang, Xi1 (AUTHOR) yangxi@stu.xupt.edu.cn, Wu, Chengmao2 (AUTHOR), Zhang, Rui1,2 (AUTHOR)
Publikováno v:
Journal of Intelligent & Fuzzy Systems. 2024Supplement, Vol. 17, p515-531. 17p.
Autor:
Wu, Chengmao1 (AUTHOR) wuchengmao@xiyou.edu.cn, Zhou, Siyu1 (AUTHOR) zhousiyu0915@163.com
Publikováno v:
Symmetry (20738994). Oct2024, Vol. 16 Issue 10, p1370. 48p.
Autor:
Artiaco, Claudia, Kvorning, Thomas Klein, Chávez, David Aceituno, Herviou, Loïc, Bardarson, Jens H.
We propose a universal framework for classifying quantum states based on their scale-resolved correlation structure. Using the recently introduced information lattice, which provides an operational definition of the total amount of correlations at ea
Externí odkaz:
http://arxiv.org/abs/2410.10971
Autor:
Mrani-Zentar, Omar, Yüksel, Serdar
Decentralized stochastic control problems are intrinsically difficult to study because of the inapplicability of standard tools from centralized control such as dynamic programming and the resulting computational complexity. In this paper, we address
Externí odkaz:
http://arxiv.org/abs/2408.13828
Although several image super-resolution solutions exist, they still face many challenges. CNN-based algorithms, despite the reduction in computational complexity, still need to improve their accuracy. While Transformer-based algorithms have higher ac
Externí odkaz:
http://arxiv.org/abs/2405.01085