Zobrazeno 1 - 10
of 218
pro vyhledávání: '"Chen, Lixing"'
STOchastic Recursive Momentum (STORM)-based algorithms have been widely developed to solve one to $K$-level ($K \geq 3$) stochastic optimization problems. Specifically, they use estimators to mitigate the biased gradient issue and achieve near-optima
Externí odkaz:
http://arxiv.org/abs/2407.05286
Multi-agent perception (MAP) allows autonomous systems to understand complex environments by interpreting data from multiple sources. This paper investigates intermediate collaboration for MAP with a specific focus on exploring "good" properties of c
Externí odkaz:
http://arxiv.org/abs/2403.10068
Autor:
Zhu, Yinghao, Peng, Di, Zhang, Enkang, Pan, Bingying, Chen, Xu, Chen, Lixing, Ren, Huifen, Liu, Feiyang, Hao, Yiqing, Li, Nana, Xing, Zhenfang, Lan, Fujun, Han, Jiyuan, Wang, Junjie, Jia, Donghan, Wo, Hongliang, Gu, Yiqing, Gu, Yimeng, Ji, Li, Wang, Wenbin, Gou, Huiyang, Shen, Yao, Ying, Tianping, Chen, Xiaolong, Yang, Wenge, Cao, Huibo, Zheng, Changlin, Zeng, Qiaoshi, Guo, Jian-gang, Zhao, Jun
Publikováno v:
Nature 631, 531-536 (2024)
The pursuit of discovering new high-temperature superconductors that diverge from the copper-based paradigm1-3 carries profound implications for elucidating mechanisms behind superconductivity and may also enable new applications4-8. Here, our invest
Externí odkaz:
http://arxiv.org/abs/2311.07353
Publikováno v:
In Preventive Medicine Reports November 2024 47
The rapid uptake of intelligent applications is pushing deep learning (DL) capabilities to Internet-of-Things (IoT). Despite the emergence of new tools for embedding deep neural networks (DNNs) into IoT devices, providing satisfactory Quality of Expe
Externí odkaz:
http://arxiv.org/abs/2112.06918
Federated Learning (FL) has been considered as an appealing framework to tackle data privacy issues of mobile devices compared to conventional Machine Learning (ML). Using Edge Servers (ESs) as intermediaries to perform model aggregation in proximity
Externí odkaz:
http://arxiv.org/abs/2112.00925
Autor:
Yu, Fangming, He, Ziang, Xin, Xiaomin, Shi, Xinwei, Chen, Lixing, He, Xinying, Huang, Yueying, Li, Yi
Publikováno v:
In Journal of Hazardous Materials 5 December 2024 480
Publikováno v:
In Computers & Security July 2024 142
Recent breakthroughs in deep learning (DL) have led to the emergence of many intelligent mobile applications and services, but in the meanwhile also pose unprecedented computing challenges on resource-constrained mobile devices. This paper builds a c
Externí odkaz:
http://arxiv.org/abs/2102.02638
This paper studies a federated learning (FL) system, where \textit{multiple} FL services co-exist in a wireless network and share common wireless resources. It fills the void of wireless resource allocation for multiple simultaneous FL services in th
Externí odkaz:
http://arxiv.org/abs/2101.03627