1.2k citations · 9.5k across the 261 of their papers we have counts for
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Semantics Alignment via Split Learning for Resilient Multi-User Semantic Communication
Jinhyuk Choi, Jihong Park, Seung-Woo Ko +3
Recent studies on semantic communication commonly rely on neural network (NN) based transceivers such as deep joint source and channel coding (DeepJSCC). Unlike traditional transce…
Deep Reinforcement Learning Algorithms for Hybrid V2X Communication: A Benchmarking Study
Fouzi Boukhalfa, Reda Alami, Mastane Achab +2
In today's era, autonomous vehicles demand a safety level on par with aircraft. Taking a cue from the aerospace industry, which relies on redundancy to achieve high reliability, th…
Emergent Communication in Multi-Agent Reinforcement Learning for Future Wireless Networks
Marwa Chafii, Salmane Naoumi, Reda Alami +3
In different wireless network scenarios, multiple network entities need to cooperate in order to achieve a common task with minimum delay and energy consumption. Future wireless ne…
Federated Learning Games for Reconfigurable Intelligent Surfaces via Causal Representations
Charbel Bou Chaaya, Sumudu Samarakoon, Mehdi Bennis
In this paper, we investigate the problem of robust Reconfigurable Intelligent Surface (RIS) phase-shifts configuration over heterogeneous communication environments. The problem i…
Cooperative Multi-Agent Learning for Navigation via Structured State Abstraction
Mohamed K. Abdelaziz, Mohammed S. Elbamby, Sumudu Samarakoon +1
Cooperative multi-agent reinforcement learning (MARL) for navigation enables agents to cooperate to achieve their navigation goals. Using emergent communication, agents learn a com…
On the Energy and Communication Efficiency Tradeoffs in Federated and Multi-Task Learning
Stefano Savazzi, Vittorio Rampa, Sanaz Kianoush +1
Recent advances in Federated Learning (FL) have paved the way towards the design of novel strategies for solving multiple learning tasks simultaneously, by leveraging cooperation a…