[ad_1] Introduction Generative adversarial networks (GANs) have gained significant attention in the field of deep learning for their ability to generate realistic and high-quality data, including images, text, and even 3D objects. In recent years,…
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[ad_1] Introduction 1.1 Introduction 1.2 Background of study 1.3 Problem Statement 1.4 Objective of study 1.5 Limitation of study 1.6 Scope of study 1.7 Significance of study 1.8 Structure of the Thesis 1.9 Definition of…
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[ad_1] Introduction The rise of quantum computing technology poses a significant threat to the security of current key exchange protocols used in cryptographic systems. Quantum computers have the potential to break traditional encryption schemes, rendering…
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[ad_1] Introduction: Zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARKs) have emerged as a powerful tool for enhancing the scalability and privacy of blockchain networks. These cryptographic protocols allow for the verification of computations without revealing…
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[ad_1] Introduction In today’s digital age, personalized recommendations and content are essential for providing an engaging and tailored user experience across various devices. Federated transfer learning, a cutting-edge technique in machine learning, offers a promising…
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[ad_1] Introduction In recent years, the field of machine learning has seen significant advancements with the introduction of quantum computing. Quantum machine learning combines the principles of quantum mechanics with traditional machine learning algorithms to…
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[ad_1] Introduction Decentralized prediction markets have gained significant attention in recent years due to their potential to revolutionize the way individuals predict and exchange information about future events. By utilizing blockchain technology, these prediction markets…
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[ad_1] Introduction In recent years, machine learning algorithms have shown significant potential in providing decision support for various domains, including healthcare. However, the black-box nature of many machine learning models often poses challenges in their…
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[ad_1] Introduction Differential privacy has emerged as a promising technique for protecting the privacy of individuals in datasets while allowing for meaningful analysis to be conducted. With the rise of federated analytics, which involves the…
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[ad_1] Introduction Quantum error correction is a crucial component in the development of fault-tolerant quantum computing. With the potential to revolutionize computing capabilities, quantum computing offers the possibility of solving problems that are currently intractable…
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