34 citations · 51 across the 11 of their papers we have counts for
11 papers
Cooperative Multi-Task Semantic Communication for Joint Classification and Regression Tasks
Ahmad Halimi Razlighi, Mohammad Siddiqur Rahman, Maximilian H. V. Tillmann +2
Multi-Task semantic communication (SemCom) prioritizes simultaneous execution of multiple tasks over bit-accurate reconstruction in future intelligent networks. In our prior work […
Semantic-Aware Task Clustering for Constructive and Cooperative Multi-Tasking
Ahmad Halimi Razlighi, Maximilian H. V. Tillmann, Edgar Beck +2
Cooperative multi-task semantic communication (CMT-SemCom) improves task execution performance by leveraging shared representations. However, as we demonstrated in [1], cooperative…
Semantic-Aware Task Clustering for Federated Cooperative Multi-Task Semantic Communication
Ahmad Halimi Razlighi, Pallavi Dhingra, Edgar Beck +2
Task-oriented semantic communication (SemCom) prioritizes task execution over accurate symbol reconstruction and is well-suited to emerging intelligent applications. Cooperative mu…
Integrating Semantic Communication and Human Decision-Making into an End-to-End Sensing-Decision Framework
Edgar Beck, Hsuan-Yu Lin, Patrick Rückert +5
As early as 1949, Weaver defined communication in a very broad sense to include all procedures by which one mind or technical system can influence another, thus establishing the id…
Cooperative and Collaborative Multi-Task Semantic Communication for Distributed Sources
Ahmad Halimi Razlighi, Maximilian H. V. Tillmann, Edgar Beck +2
In this paper, we explore a multi-task semantic communication (SemCom) system for distributed sources, extending the existing focus on collaborative single-task execution. We build…
Model-free Reinforcement Learning of Semantic Communication by Stochastic Policy Gradient
Edgar Beck, Carsten Bockelmann, Armin Dekorsy
Following the recent success of Machine Learning tools in wireless communications, the idea of semantic communication by Weaver from 1949 has gained attention. It breaks with Shann…
Robust Deep Reinforcement Learning Scheduling via Weight Anchoring
Steffen Gracla, Edgar Beck, Carsten Bockelmann +1
Questions remain on the robustness of data-driven learning methods when crossing the gap from simulation to reality. We utilize weight anchoring, a method known from continual lear…
Learning Resource Scheduling with High Priority Users using Deep Deterministic Policy Gradients
Steffen Gracla, Edgar Beck, Carsten Bockelmann +1
Advances in mobile communication capabilities open the door for closer integration of pre-hospital and in-hospital care processes. For example, medical specialists can be enabled t…
Semantic Information Recovery in Wireless Networks
Edgar Beck, Carsten Bockelmann, Armin Dekorsy
Motivated by the recent success of Machine Learning (ML) tools in wireless communications, the idea of semantic communication by Weaver from 1949 has gained attention. It breaks wi…
Deep Reinforcement Model Selection for Communications Resource Allocation in On-Site Medical Care
Steffen Gracla, Edgar Beck, Carsten Bockelmann +1
Greater capabilities of mobile communications technology enable interconnection of on-site medical care at a scale previously unavailable. However, embedding such critical, demandi…
CMDNet: Learning a Probabilistic Relaxation of Discrete Variables for Soft Detection with Low Complexity
Edgar Beck, Carsten Bockelmann, Armin Dekorsy
Following the great success of Machine Learning (ML), especially Deep Neural Networks (DNNs), in many research domains in 2010s, several ML-based approaches were proposed for detec…