[ad_1] Introduction: In recent years, artificial intelligence (AI) has played a significant role in revolutionizing various industries by enabling machines to perform tasks that traditionally required human intelligence. However, the centralized nature of traditional AI…
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[ad_1] Introduction In recent times, with the rapid advancements in technology and the widespread use of cloud computing, the need for secure and confidential data processing has become more important than ever. Encrypted computation is…
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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 Homomorphic encryption is a groundbreaking technology that allows for computations to be performed on encrypted data without the need to decrypt it. This offers a powerful tool for privacy-preserving computation, ensuring that sensitive…
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[ad_1] Introduction Privacy-preserving machine learning for secure computation is a rapidly growing field in computer science and data privacy. With the increasing amount of sensitive data being collected and analyzed, ensuring the privacy and security…
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[ad_1] Introduction: Distributed optimization for decentralized learning has gained increasing attention in recent years due to the proliferation of IoT devices and edge computing technologies. These technologies enable data to be processed closer to where…
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[ad_1] Introduction Convex optimization is a powerful mathematical tool that has been widely used in various fields such as machine learning, signal processing, control systems, and operations research. It involves the optimization of convex objective…
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[ad_1] Introduction: In recent years, there has been a growing interest in submodular optimization for diversity and coverage in various fields such as machine learning, data mining, and artificial intelligence. Submodular functions have the property…
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[ad_1] Introduction Dictionary learning is a powerful technique used in machine learning and signal processing for basis discovery. It involves the process of learning a dictionary that can effectively represent a set of data samples…
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[ad_1] Introduction Sparse coding is a powerful technique in the field of machine learning and signal processing that aims to efficiently represent data using a small number of non-zero coefficients. It has been widely used…
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