The Quantum Approximate Optimization Algorithm (QAOA) has emerged as a promising approach for solving NP-hard combinatorial optimization problems on noisy intermediate-scale quantum (NISQ) hardware. However, its performance critically depends on the choice of circuit depth–a parameter that must be specified a priori wi...
Rakesh Saini, Nora Mohamed, S. Al-Kuwari et al.· Quantum Machine Intelligence· 0 citations
This survey examines how LAMs can support communication intelligence in HC-IoT by combining perception, reasoning, and real-time control and presents a unified taxonomy and architectural framework for HC-IoT applications using LAMs to manage latency, reliability, throughput, and resource allocation across medical netwo...
Muhammad Adil, H. Song, Safayat Bin Hakim et al.· IEEE Open Journal of the Com...· 0 citations
Quantumer, a hybrid TinyML--quantum framework that integrates multi-scale dilated convolutions and scaled dot-product attention within a lightweight transformer architecture, employing a two-stage transfer learning pipeline from Quantum Pre-Training (Quantumer-Q) to Classical Fine-Tuning (Quantumer-C).
M. B. A. Dastagir, Rakesh Saini, Omer Tariq et al.· 0 citations
This article addresses challenges in the Internet of Consumer Electronics (ICE), such as random task arrivals, limited resources, and system stability, by proposing a collaborative computing framework that integrates edge intelligence with Lyapunov-based deep reinforcement learning (DRL). The framework adopts a three-t...
Yongtao Yao, Miaojiang Chen, Meng Yi et al.· IEEE Consumer Electronics Ma...· 0 citations
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