[ad_1] Introduction Blockchain technology has gained significant popularity in recent years, revolutionizing various industries with its decentralized and secure nature. One of the areas where blockchain has the potential to make a significant impact is…
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[ad_1] Introduction Quantum machine learning (QML) has emerged as a promising field that combines quantum computing with machine learning algorithms to solve complex problems in various domains. In recent years, researchers have started exploring the…
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[ad_1] Introduction: Privacy-preserving machine learning is a crucial area of research in the context of smart cities, where large volumes of data are collected from various sources to improve the quality of services and infrastructure.…
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[ad_1] Introduction Space debris, also known as space junk, poses a significant threat to active satellites, spacecraft, and astronauts in orbit. With the increasing number of satellites being launched into space, the risk of collisions…
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[ad_1] Introduction In the era of big data and artificial intelligence, the financial services industry is constantly seeking new ways to leverage data for improved decision-making and customer service. However, the sensitive nature of financial…
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[ad_1] Introduction Natural language generation (NLG) refers to the process of producing human-like text or speech from data or information. In recent years, NLG has gained significant attention due to its potential applications in various…
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[ad_1] Introduction Social networks have become an integral part of our daily lives, with millions of users sharing personal information, photos, and interactions on various platforms. However, the vast amount of data generated by these…
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[ad_1] Introduction Swarm robotics is a relatively new field of research that draws inspiration from the collective behavior of social insects such as ants and bees. These robots are capable of collaborating with each other…
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[ad_1] Introduction The use of reinforcement learning in autonomous trading systems has gained significant attention due to its ability to adapt and learn from market data to make informed trading decisions. This thesis aims to…
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[ad_1] Introduction Federated learning has emerged as a promising approach for collaborative machine learning across multiple data silos, where data cannot be centrally aggregated due to privacy or regulatory concerns. This thesis aims to explore…
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