activity
20172026
most citedMulti-Armed Bandit Based Client Scheduling for Federated Learning

313 citations · 654 across the 61 of their papers we have counts for

collaborators
Showing 2024Show all

11 papers · 1 filter

cs.NI2024

Age of Information in Random Access Networks with Energy Harvesting

Fangming Zhao, Nikolaos Pappas, Meng Zhang +1

We study the age of information (AoI) in a random access network consisting of multiple source-destination pairs, where each source node is empowered by energy harvesting capabilit…

cs.LG2024

Robust Federated Learning Over the Air: Combating Heavy-Tailed Noise with Median Anchored Clipping

Jiaxing Li, Zihan Chen, Kai Fong Ernest Chong +3

Leveraging over-the-air computations for model aggregation is an effective approach to cope with the communication bottleneck in federated edge learning. By exploiting the superpos…

cs.LG2024★ 1 cited

Towards General Industrial Intelligence: A Survey of Continual Large Models in Industrial IoT

Jiao Chen, Jiayi He, Fangfang Chen +6

Industrial AI is transitioning from traditional deep learning models to large-scale transformer-based architectures, with the Industrial Internet of Things (IIoT) playing a pivotal…

cs.IT2024

Trustworthy Image Semantic Communication with GenAI: Explainablity, Controllability, and Efficiency

Xijun Wang, Dongshan Ye, Chenyuan Feng +3

Image semantic communication (ISC) has garnered significant attention for its potential to achieve high efficiency in visual content transmission. However, existing ISC systems bas…

cs.IT2024

Timeliness of Status Update System: The Effect of Parallel Transmission Using Heterogeneous Updating Devices

Zhengchuan Chen, Kang Lang, Nikolaos Pappas +4

Timely status updating is the premise of emerging interaction-based applications in the Internet of Things (IoT). Using redundant devices to update the status of interest is a prom…

cs.IT2024

The Meta Distribution of the SIR in Joint Communication and Sensing Networks

Kun Ma, Chenyuan Feng, Giovanni Geraci +1

In this paper, we introduce a novel mathematical framework for assessing the performance of joint communication and sensing (JCAS) in wireless networks, employing stochastic geomet…