Profil bibliographique

Dinh Cong Nguyen

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31Publications signalées
84Citations signalées
1Affiliations récentes

Les institutions déclarées

Hồng Đức University

Les domaines associés

Advanced Neural Network ApplicationsHandwritten Text Recognition TechniquesAdvanced Image and Video Retrieval TechniquesPrivacy-Preserving Technologies in DataQuantum Information and Cryptography

Les publications récentes

Accès ouvert 2026 preprint OpenAlex

Tackling Heterogeneity in Quantum Federated Learning: An Integrated Sporadic-Personalized Approach

Ratun Rahman, Shaba Shaon, Dinh Cong Nguyen

Quantum federated learning (QFL) emerges as a powerful technique that combines quantum computing with federated learning to efficiently process complex data across distributed quantum devices while ensuring data privacy in quantum networks. Despite recent research efforts, existing QFL frameworks struggle to achieve …

0 citations arXiv (Cornell University)
Accès ouvert 2026 preprint OpenAlex

Tackling Heterogeneity in Quantum Federated Learning: An Integrated Sporadic-Personalized Approach

Ratun Rahman, Shaba Shaon, Dinh Cong Nguyen

Quantum federated learning (QFL) emerges as a powerful technique that combines quantum computing with federated learning to efficiently process complex data across distributed quantum devices while ensuring data privacy in quantum networks. Despite recent research efforts, existing QFL frameworks struggle to achieve …

0 citations arXiv (Cornell University)
Accès ouvert 2025 preprint OpenAlex

Towards Personalized Quantum Federated Learning for Anomaly Detection

Ratun Rahman, Sina Shaham, Dinh Cong Nguyen

Anomaly detection has a significant impact on applications such as video surveillance, medical diagnostics, and industrial monitoring, where anomalies frequently depend on context and anomaly-labeled data are limited. Quantum federated learning (QFL) overcomes these concerns by distributing model training among several quantum …

0 citations arXiv (Cornell University)
Accès ouvert 2025 preprint OpenAlex

Latency-aware Multimodal Federated Learning over UAV Networks

Shaba Shaon, Dinh Cong Nguyen

This paper investigates federated multimodal learning (FML) assisted by unmanned aerial vehicles (UAVs) with a focus on minimizing system latency and providing convergence analysis. In this framework, UAVs are distributed throughout the network to collect data, participate in model training, and collaborate …

0 citations arXiv (Cornell University)
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