19 papers
Quantum Noise Mitigation with Adaptive Zero-Noise Extrapolation: A Contextual Multi-Armed Bandits Approach
Ratun Rahman, Dinh C. Nguyen
Variational quantum circuits (VQCs) are central to near-term quantum computing, yet their practical deployment is severely hindered by noise. While existing error mitigation method…
Scalable Malware Family Classification Using Quantum Kernel Based Machine Learning
Ratun Rahman, Hassan Jalil Hadi, Christopher Gabriel Pedraza Pohlenz +1
The classification of malware families is a key challenge in cybersecurity, which enables threat attribution, analysis of attack operations, and the formulation of effective defens…
Geometric Fairness-Aware Routing for Federated Edge Networks
Ratun Rahman
Emerging 6G and edge-intelligent networks require effective and balanced routing algorithms among varied and spatially distributed devices. Existing federated routing systems often…
Probabilistic Federated Learning on Uncertain and Heterogeneous Data with Model Personalization
Ratun Rahman, Dinh C. Nguyen
Conventional federated learning (FL) frameworks often suffer from training degradation due to data uncertainty and heterogeneity across local clients. Probabilistic approaches such…
Federated Learning: A Survey on Privacy-Preserving Collaborative Intelligence
Ratun Rahman
Federated Learning (FL) has emerged as a transformative paradigm in the field of distributed machine learning, enabling multiple clients such as mobile devices, edge nodes, or orga…
Tackling Heterogeneity in Quantum Federated Learning: An Integrated Sporadic-Personalized Approach
Ratun Rahman, Shaba Shaon, Dinh C. Nguyen
Quantum federated learning (QFL) emerges as a powerful technique that combines quantum computing with federated learning to efficiently process complex data across distributed quan…