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Full Description
Quantum Computational AI: Algorithms, Systems, and Applications is an emerging field that bridges quantum computing and artificial intelligence. With rapid advancements in both areas, this book serves as a vital resource, capturing the latest theories, algorithms, and practical applications at their intersection. It aims to be both informative and accessible, making it perfect for academics, researchers, industry professionals, and students eager to lead in these technologies. The book explores quantum algorithms, system design, and demonstrates real-world applications across various sectors. It provides a comprehensive understanding of how quantum principles can advance AI, revealing unprecedented possibilities and benefits.
Contents
PART 1 Algorithms
1. Quantum reinforcement learning
2. Exploring quantum federated learning
3. Temporal-spatial quantum graph convolutional neural
network
4. Quantum unsupervised machine learning
PART 2 Systems
5. Distributed learning with quantum-classical collaborative
management
6. Hybrid quantum-classical reinforcement learning for
scheduling systems
7. Efficient full-state simulation for quantum AI systems
8. Machine learning in bosonic quantum systems
PART 3 Applications
9. Quantum support vector machine for power quality analysis
10. Quantum computing for automotive applications
11. Quantum-enhanced decision-making in ACT-R
12. Quantum federated learning for speech emotion
recognition
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