[ad_1] Introduction: Chapter 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…
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[ad_1] Introduction Attention mechanisms have become a crucial component in various fields such as natural language processing, computer vision, and machine learning. These mechanisms allow models to focus on important parts of the input data…
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[ad_1] Introduction: In recent years, there has been a growing interest in developing robust machine learning models that can perform well in the presence of adversarial attacks. These attacks are designed to exploit vulnerabilities in…
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[ad_1] Introduction Multi-agent reinforcement learning (MARL) is a subfield of artificial intelligence that focuses on developing algorithms and techniques for coordinating multiple autonomous agents to achieve a common goal. The coordination of multiple agents presents…
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[ad_1] **Introduction** Swarm intelligence is a field of study that focuses on the collective behavior of decentralized, self-organizing systems. It draws inspiration from the behavior of social insects such as ants, bees, and termites, which…
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[ad_1] Introduction Smart contracts have gained popularity in recent years due to their ability to automate and facilitate secure transactions on blockchain platforms. In the field of machine learning, smart contracts can be used to…
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[ad_1] Introduction Blockchain technology has gained significant attention in recent years due to its potential to revolutionize various industries by providing decentralized, secure, and transparent systems. One area that stands to benefit greatly from the…
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[ad_1] Introduction: Secure enclaves for trusted execution have gained significant attention in recent years due to the growing concerns about the security and privacy of sensitive data in cloud computing environments. Secure enclaves, also known…
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[ad_1] Introduction Secure aggregation for distributed learning is a critical component in the field of machine learning and data privacy. With the increasing amount of data being collected and processed in various applications, the need…
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[ad_1] Introduction Federated analytics is a novel approach to decentralized learning that involves training machine learning models across multiple edge devices or servers while keeping the data on these devices rather than centralizing it. This…
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