12 citations · 19 across the 11 of their papers we have counts for
11 papers
SPAT: A Semantic Port-Aware Adaptive-Rate Transmission Protocol for Semantic Communication
Yunhao Wang, Shuai Ma, Bin Shen +4
With the evolution of 6G, semantic communication has emerged as a promising paradigm by prioritizing the delivery of task-relevant meaning over strict bit-level correctness. Howeve…
Optimally Bridging Semantics and Data: Generative Semantic Communication via Schrödinger Bridge
Dahua Gao, Ruichao Liu, Minxi Yang +3
Generative Semantic Communication (GSC) is a promising solution for image transmission over narrow-band and high-noise channels. However, existing GSC methods rely on long, indirec…
Modeling and Performance Analysis for Semantic Communications Based on Empirical Results
Shuai Ma, Bin Shen, Chuanhui Zhang +5
Due to the black-box characteristics of deep learning based semantic encoders and decoders, finding a tractable method for the performance analysis of semantic communications is a…
Semantic Feature Division Multiple Access for Digital Semantic Broadcast Channels
Shuai Ma, Zhiye Sun, Bin Shen +5
In this paper, we propose a digital semantic feature division multiple access (SFDMA) paradigm in multi-user broadcast (BC) networks for the inference and the image reconstruction…
Structured IB: Improving Information Bottleneck with Structured Feature Learning
Hanzhe Yang, Youlong Wu, Dingzhu Wen +2
The Information Bottleneck (IB) principle has emerged as a promising approach for enhancing the generalization, robustness, and interpretability of deep neural networks, demonstrat…
Towards Effective and Interpretable Semantic Communications
Youlong Wu, Yuanmin Shi, Shuai Ma +3
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 disrupti…
Semantic Feature Division Multiple Access for Multi-user Digital Interference Networks
Shuai Ma, Chuanhui Zhang, Bin Shen +5
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 challen…
Task-Oriented Lossy Compression with Data, Perception, and Classification Constraints
Yuhan Wang, Youlong Wu, Shuai Ma +1
By extracting task-relevant information while maximally compressing the input, the information bottleneck (IB) principle has provided a guideline for learning effective and robust…
Privacy for Fairness: Information Obfuscation for Fair Representation Learning with Local Differential Privacy
Songjie Xie, Youlong Wu, Jiaxuan Li +2
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 h…
Coded Computing for Half-Duplex Wireless Distributed Computing Systems via Interference Alignment
Youlong Wu, Zhenhao Huang, Kai Yuan +2
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 nod…
Robust Power Allocation for UAV-aided ISAC Systems with Uncertain Location Sensing Errors
Junchang Sun, Shuai Ma, Ruixin Yang +2
Unmanned aerial vehicle (UAV) holds immense potential in integrated sensing and communication (ISAC) systems for the Internet of Things (IoT). In this paper, we propose a UAV-aided…