23 citations · 31 across the 12 of their papers we have counts for
12 papers
Trust Region Bayesian Optimization of Annealing Schedules on a Quantum Annealer
Seon-Geun Jeong, Mai Dinh Cong, Minh-Duong Nguyen +3
Quantum annealing (QA) is a practical model of adiabatic quantum computation, already realized on hardware and considered promising for combinatorial optimization. However, its per…
Communication-Efficient and Accurate Approach for Aggregation in Federated Low-Rank Adaptation
Le-Tuan Nguyen, Minh-Duong Nguyen, Seon-Geun Jeong +2
With the rapid emergence of foundation models and the increasing need for fine-tuning across distributed environments, Federated Low-Rank Adaptation (FedLoRA) has recently gained s…
Enhancing Gradient Variance and Differential Privacy in Quantum Federated Learning
Duc-Thien Phan, Minh-Duong Nguyen, Quoc-Viet Pham +1
Upon integrating Quantum Neural Network (QNN) as the local model, Quantum Federated Learning (QFL) has recently confronted notable challenges. Firstly, exploration is hindered over…
Knowledge Abstraction for Knowledge-based Semantic Communication: A Generative Causality Invariant Approach
Minh-Duong Nguyen, Quoc-Viet Pham, Nguyen H. Tran +3
In this study, we design a low-complexity and generalized AI model that can capture common knowledge to improve data reconstruction of the channel decoder for semantic communicatio…
Improving Generalization in Heterogeneous Federated Continual Learning via Spatio-Temporal Gradient Matching with Prototypical Coreset
Minh-Duong Nguyen, Le-Tuan Nguyen, Quoc-Viet Pham
Federated Continual Learning (FCL) has recently emerged as a crucial research area, as data from distributed clients typically arrives as a stream, requiring sequential learning. T…
Multi-Agent Collaboration Mechanisms: A Survey of LLMs
Khanh-Tung Tran, Dung Dao, Minh-Duong Nguyen +3
With recent advances in Large Language Models (LLMs), Agentic AI has become phenomenal in real-world applications, moving toward multiple LLM-based agents to perceive, learn, reaso…
Applications of Generative AI (GAI) for Mobile and Wireless Networking: A Survey
Thai-Hoc Vu, Senthil Kumar Jagatheesaperumal, Minh-Duong Nguyen +3
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 tow…
Energy-Efficient and Real-Time Sensing for Federated Continual Learning via Sample-Driven Control
Minh Ngoc Luu, Minh-Duong Nguyen, Ebrahim Bedeer +4
An intelligent Real-Time Sensing (RTS) system must continuously acquire, update, integrate, and apply knowledge to adapt to real-world dynamics. Managing distributed intelligence i…
Distortion Resilience for Goal-Oriented Semantic Communication
Minh-Duong Nguyen, Quang-Vinh Do, Zhaohui Yang +2
Recent research efforts on Semantic Communication (SemCom) have mostly considered accuracy as a main problem for optimizing goal-oriented communication systems. However, these appr…
Label driven Knowledge Distillation for Federated Learning with non-IID Data
Minh-Duong Nguyen, Quoc-Viet Pham, Dinh Thai Hoang +3
In real-world applications, Federated Learning (FL) meets two challenges: (1) scalability, especially when applied to massive IoT networks; and (2) how to be robust against an envi…
Resource Allocation for Compression-aided Federated Learning with High Distortion Rate
Xuan-Tung Nguyen, Minh-Duong Nguyen, Quoc-Viet Pham +2
Recently, a considerable amount of works have been made to tackle the communication burden in federated learning (FL) (e.g., model quantization, data sparsification, and model comp…
HCFL: A High Compression Approach for Communication-Efficient Federated Learning in Very Large Scale IoT Networks
Minh-Duong Nguyen, Sang-Min Lee, Quoc-Viet Pham +3
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 centra…