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Quantum-inspired optimization for facility location problems – Complete Phd and Masters Thesis

[ad_1] Introduction Quantum-inspired optimization, based on principles of quantum mechanics, has emerged as a promising approach for solving complex optimization problems efficiently. Facility location problems are important in various real-world applications such as supply chain…

Interpretable machine learning for healthcare risk prediction – Complete Phd and Masters Thesis

[ad_1] Introduction In recent years, there has been a significant increase in the use of machine learning algorithms in healthcare for various applications, including risk prediction, diagnostic imaging, personalized treatment, and data-driven decision making. However,…

Differential privacy for privacy-preserving graph analytics – Complete Phd and Masters Thesis

[ad_1] Introduction With the proliferation of data in today’s digital age, privacy concerns have become increasingly important. This is particularly true for graph data, which often contains sensitive information about individuals and organizations. In order…

Zero-shot learning for relation extraction – Complete Phd and Masters Thesis

[ad_1] Introduction: Zero-shot learning for relation extraction is an emerging field in natural language processing that aims to extract relations between entities without requiring any labeled training data for those specific relations. Traditional relation extraction…

Federated reinforcement learning for edge computing optimization – Complete Phd and Masters Thesis

[ad_1] Introduction With the rapid growth of Internet of Things (IoT) devices and the increasing demand for real-time data processing, edge computing has emerged as a promising solution to address the limitations of cloud computing.…

Neuromorphic computing for spiking neural networks – Complete Phd and Masters Thesis

[ad_1] Introduction Neuromorphic computing has emerged as a promising approach to developing brain-inspired computing systems that mimic the behavior of the human brain. Spiking neural networks, which are based on the principles of biological neural…

Distributed ledger technology for decentralized finance (DeFi) – Complete Phd and Masters Thesis

[ad_1] Introduction Distributed ledger technology (DLT), which emerged as the underlying technology of cryptocurrencies like Bitcoin, has gained significant attention in recent years. Particularly, the application of DLT in decentralized finance (DeFi) has the potential…

Homomorphic encryption for secure image processing – Complete Phd and Masters Thesis

[ad_1] Introduction Homomorphic encryption is a revolutionary technology that allows computations to be performed directly on encrypted data without the need to decrypt it. This breakthrough in cryptography has significant implications for secure image processing,…

Zero-knowledge proofs for privacy-preserving smart metering – Complete Phd and Masters Thesis

[ad_1] Introduction Zero-knowledge proofs have gained significant attention in recent years for their potential to enhance privacy in various applications, including smart metering systems. Smart meters are essential components of modern energy grids, providing real-time…

Generative adversarial networks for video prediction – Complete Phd and Masters Thesis

[ad_1] Thesis Overview: Title: Generative Adversarial Networks for Video Prediction Introduction: Generative adversarial networks (GANs) have gained significant attention in recent years for their ability to generate realistic data samples. Video prediction is a challenging…

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