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Zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARKs) for verifiable multi-party computation – Complete Phd and Masters Thesis

[ad_1] Introduction Zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARKs) have emerged as a powerful cryptographic tool for verifiable multi-party computation. In this thesis, we explore the application of zk-SNARKs in facilitating secure and efficient multi-party…

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

[ad_1] Introduction Quantum machine learning (QML) has emerged as a promising field at the intersection of quantum computing and machine learning. With the potential for exponential speedup in certain computational tasks, quantum algorithms have the…

Decentralized voting systems using blockchain – Complete Phd and Masters Thesis

[ad_1] Introduction In recent years, the use of blockchain technology has gained significant attention in various industries due to its transparency, security, and decentralization. One particular area where blockchain technology has the potential to revolutionize…

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…

Multi-modal learning for audio-visual event localization – Complete Phd and Masters Thesis

[ad_1] **Introduction** The advancement of technology has led to an abundance of audio-visual data, making it essential to develop efficient methods for analyzing and localizing events in multimedia content. Multi-modal learning, which leverages both audio…

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…

Quantum error correction for quantum cryptography – Complete Phd and Masters Thesis

[ad_1] Introduction Quantum cryptography is a rapidly developing field that promises secure communication through the use of quantum mechanics principles. However, quantum systems are susceptible to errors due to noise and imperfections in the physical…

Graph neural networks for knowledge graph completion – Complete Phd and Masters Thesis

[ad_1] Introduction: The field of graph neural networks has emerged as a powerful tool for analyzing and processing complex data with graph structures. In recent years, there has been a growing interest in using graph…

Transfer learning for cross-modal sentiment analysis – Complete Phd and Masters Thesis

[ad_1] Introduction In recent years, sentiment analysis has gained significant attention in various application domains such as social media, e-commerce, and customer feedback analysis. Sentiment analysis aims to identify and extract subjective information from textual…

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