[ad_1] Introduction: Secure Multi-Party Computation (SMPC) is a cryptographic technique that allows multiple parties to jointly compute a function over their private inputs without revealing any individual input to the other parties. This technology has…
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[ad_1] Introduction: In recent years, the rapid advancement of artificial intelligence (AI) and data science technologies has led to significant ethical concerns regarding the implications of their use in various applications. It is essential for…
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[ad_1] Introduction: Generative Models for Data Augmentation is a rapidly growing field in machine learning and artificial intelligence that focuses on generating new training data from existing data to improve the performance of machine learning…
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[ad_1] Introduction: Distributed Optimization for Large-Scale Machine Learning is a vital area within the field of machine learning, particularly as datasets continue to grow exponentially in size and complexity. This thesis aims to explore the…
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[ad_1] Introduction: Anomaly detection in sensor data plays a crucial role in ensuring the security and reliability of IoT networks. With the increasing number of devices connected to the internet, the need for efficient anomaly…
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[ad_1] Introduction: Streaming data processing techniques have become increasingly important in the field of data analytics as the volume and velocity of data continue to grow exponentially. This has led to the development of various…
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[ad_1] Introduction: Multi-Agent Reinforcement Learning (MARL) has gained significant attention in recent years due to its ability to model complex collaborative systems where multiple agents interact with each other to achieve a common goal. MARL…
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[ad_1] Introduction: Domain adaptation is a subfield of transfer learning that focuses on the problem of adapting models trained on a source domain to perform well on a target domain that may have different distributions…
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[ad_1] Topological Data Analysis (TDA) is a powerful tool for exploring and analyzing high-dimensional data sets, which are becoming increasingly common in many fields such as biology, finance, and social sciences. TDA utilizes the mathematical…
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[ad_1] Introduction: Deep Reinforcement Learning (DRL) has gained significant attention in recent years for its ability to effectively train agents to perform complex tasks through trial and error. This technology has shown great potential in…
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