Zobrazeno 1 - 10
of 187
pro vyhledávání: '"Wu, Youlong"'
With the exponential surge in traffic data and the pressing need for ultra-low latency in emerging intelligence applications, it is envisioned that 6G networks will demand disruptive communication technologies to foster ubiquitous intelligence and su
Externí odkaz:
http://arxiv.org/abs/2408.04825
Autor:
Ma, Shuai, Zhang, Chuanhui, Shen, Bin, Wu, Youlong, Li, Hang, Li, Shiyin, Shi, Guangming, Al-Dhahir, Naofal
With the ever-increasing user density and quality of service (QoS) demand,5G networks with limited spectrum resources are facing massive access challenges. To address these challenges, in this paper, we propose a novel discrete semantic feature divis
Externí odkaz:
http://arxiv.org/abs/2407.08424
By extracting task-relevant information while maximally compressing the input, the information bottleneck (IB) principle has provided a guideline for learning effective and robust representations of the target inference. However, extending the idea t
Externí odkaz:
http://arxiv.org/abs/2405.04144
As machine learning (ML) becomes more prevalent in human-centric applications, there is a growing emphasis on algorithmic fairness and privacy protection. While previous research has explored these areas as separate objectives, there is a growing rec
Externí odkaz:
http://arxiv.org/abs/2402.10473
The distributed linearly separable computation problem finds extensive applications across domains such as distributed gradient coding, distributed linear transform, real-time rendering, etc. In this paper, we investigate this problem in a fully dece
Externí odkaz:
http://arxiv.org/abs/2401.16181
In this paper, we study the coded caching scheme for the $(K,L,M_{\text{T}},M_{\text{U}},N)$ partially connected linear network, where there are $N$ files each of which has an equal size, $K+L-1$ transmitters and $K$ users; each user and transmitter
Externí odkaz:
http://arxiv.org/abs/2310.17931
Distributed computing frameworks such as MapReduce and Spark are often used to process large-scale data computing jobs. In wireless scenarios, exchanging data among distributed nodes would seriously suffer from the communication bottleneck due to lim
Externí odkaz:
http://arxiv.org/abs/2310.15598
Distributed learning has become a promising computational parallelism paradigm that enables a wide scope of intelligent applications from the Internet of Things (IoT) to autonomous driving and the healthcare industry. This paper studies distributed l
Externí odkaz:
http://arxiv.org/abs/2310.11998
Coded distributed computing (CDC), proposed by Li et al., offers significant potential for reducing the communication load in MapReduce computing systems. In the setting of the cascaded CDC that consisting of $K$ nodes, $N$ input files, and $Q$ outpu
Externí odkaz:
http://arxiv.org/abs/2307.14927
Integrated visible light positioning and communication (VLPC), capable of combining advantages of visible light communications (VLC) and visible light positioning (VLP), is a promising key technology for the future Internet of Things. In VLPC network
Externí odkaz:
http://arxiv.org/abs/2305.09923