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Quantum machine learning for quantum tomography – Complete Phd and Masters Thesis

[ad_1] Introduction Quantum machine learning has emerged as a promising field that combines the principles of quantum mechanics and machine learning to solve complex problems efficiently. In this study, we focus on the application of…

Quantum-inspired optimization for job shop scheduling – Complete Phd and Masters Thesis

[ad_1] Introduction Quantum-inspired optimization is a cutting-edge computational technique that leverages principles from quantum mechanics to solve complex optimization problems. In recent years, researchers have been exploring the potential of quantum-inspired optimization algorithms for various…

Interpretable machine learning for credit card fraud detection – Complete Phd and Masters Thesis

[ad_1] Introduction In recent years, the increase in online transactions has led to a rise in credit card fraud cases. This has necessitated the development of more sophisticated fraud detection systems to protect consumers and…

Quantum error correction for quantum key distribution – Complete Phd and Masters Thesis

[ad_1] Introduction: Quantum key distribution (QKD) has emerged as a promising technology for secure communication, leveraging the principles of quantum mechanics to enable the distribution of encryption keys with unconditional security. However, the practical implementation…

Federated reinforcement learning for intelligent energy management – Complete Phd and Masters Thesis

[ad_1] Introduction: In recent years, there has been an increasing focus on intelligent energy management systems that can optimize energy usage and reduce waste. One promising approach to achieving this goal is through the use…

Quantum key distribution for secure mobile communication – Complete Phd and Masters Thesis

[ad_1] Introduction Quantum key distribution (QKD) is a revolutionary technology that uses the principles of quantum mechanics to provide secure communication channels. With the increasing reliance on mobile communication devices for sensitive transactions and data…

Neuromorphic computing for event-based vision – Complete Phd and Masters Thesis

[ad_1] Introduction Neuromorphic computing is a cutting-edge technology that mimics the structure and function of the human brain using electronic circuits. This emerging field has shown great potential in revolutionizing artificial intelligence and computer vision…

Zero-knowledge proofs for privacy-preserving machine learning – Complete Phd and Masters Thesis

[ad_1] Introduction: Privacy-preserving machine learning has become increasingly important in a world where data privacy is a major concern. Zero-knowledge proofs offer a promising solution to this issue by allowing parties to prove the validity…

Reinforcement learning for adaptive video streaming – Complete Phd and Masters Thesis

[ad_1] Introduction Reinforcement learning (RL) is a powerful machine learning technique that has gained significant attention in recent years due to its ability to enable intelligent decision-making in dynamic and uncertain environments. One such application…

Federated transfer learning for cross-device anomaly detection – Complete Phd and Masters Thesis

[ad_1] Introduction: In recent years, with the rapid advancement of technology and the proliferation of smart devices, the need for effective anomaly detection techniques has become crucial. Anomaly detection plays a vital role in identifying…

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