no code implementations • 30 May 2024 • Thai-Hoc Vu, Senthil Kumar Jagatheesaperumal, Minh-Duong Nguyen, Nguyen Van Huynh, Sunghwan Kim, Quoc-Viet Pham
The success of Artificial Intelligence (AI) in multiple disciplines and vertical domains in recent years has promoted the evolution of mobile networking and the future Internet toward an AI-integrated Internet-of-Things (IoT) era.
1 code implementation • 11 Oct 2023 • Minh Ngoc Luu, Minh-Duong Nguyen, Ebrahim Bedeer, Van Duc Nguyen, Dinh Thai Hoang, Diep N. Nguyen, Quoc-Viet Pham
In particular, We first formulate an optimization problem that harnesses the sampling process to concurrently reduce overfitting while maximizing accuracy.
1 code implementation • 26 Sep 2023 • Minh-Duong Nguyen, Quang-Vinh Do, Zhaohui Yang, Quoc-Viet Pham, Won-Joo Hwang
Recent research efforts on semantic communication have mostly considered accuracy as a main problem for optimizing goal-oriented communication systems.
no code implementations • 29 Sep 2022 • Minh-Duong Nguyen, Quoc-Viet Pham, Dinh Thai Hoang, Long Tran-Thanh, Diep N. Nguyen, Won-Joo Hwang
Moreover, leveraging the advantages of hierarchical network design, we propose a new label-driven knowledge distillation (LKD) technique at the global server to address the second problem.
no code implementations • 2 Jun 2022 • Xuan-Tung Nguyen, Minh-Duong Nguyen, Quoc-Viet Pham, Vinh-Quang Do, Won-Joo Hwang
Based on the property of a FL model, we first determine the number of IoT devices participating in the FL process.
1 code implementation • 14 Apr 2022 • Minh-Duong Nguyen, Sang-Min Lee, Quoc-Viet Pham, Dinh Thai Hoang, Diep N. Nguyen, Won-Joo Hwang
Federated learning (FL) is a new artificial intelligence concept that enables Internet-of-Things (IoT) devices to learn a collaborative model without sending the raw data to centralized nodes for processing.