326 citations · 754 across the 39 of their papers we have counts for
5 papers · 1 filter
JEPA for AI-Native 6G: Predictive Representations and Open Challenges
Sheikh Salman Hassan, Irshad A. Meer, Almoatssimbillah Saifaldawla +9
Sixth-generation (6G) networks are moving toward AI-native operation, where learning modules are embedded across the radio access network (RAN), edge, and core. This transition req…
An Efficient Federated Learning Framework for Training Semantic Communication System
Loc X. Nguyen, Huy Q. Le, Ye Lin Tun +4
Semantic communication has emerged as a pillar for the next generation of communication systems due to its capabilities in alleviating data redundancy. Most semantic communication…
Toward Multiple Federated Learning Services Resource Sharing in Mobile Edge Networks
Minh N. H. Nguyen, Nguyen H. Tran, Yan Kyaw Tun +2
Federated Learning is a new learning scheme for collaborative training a shared prediction model while keeping data locally on participating devices. In this paper, we study a new…
An Incentive Mechanism for Federated Learning in Wireless Cellular network: An Auction Approach
Tra Huong Thi Le, Nguyen H. Tran, Yan Kyaw Tun +4
Federated Learning (FL) is a distributed learning framework that can deal with the distributed issue in machine learning and still guarantee high learning performance. However, it…
A Crowdsourcing Framework for On-Device Federated Learning
Shashi Raj Pandey, Nguyen H. Tran, Mehdi Bennis +3
Federated learning (FL) rests on the notion of training a global model in a decentralized manner. Under this setting, mobile devices perform computations on their local data before…