[ad_1] Introduction: Multimodal learning is a growing field in machine learning that focuses on integrating information from multiple modalities to improve the performance of learning systems. Multimodal data fusion refers to the process of combining…
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[ad_1] Introduction: Graph Neural Networks (GNNs) have emerged as a powerful tool for analyzing and making predictions on graph-structured data. Knowledge graphs, which represent structured information about entities and their relationships, are a common form…
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[ad_1] Introduction: Transfer learning has gained significant attention in recent years as a powerful technique for improving the performance of natural language understanding systems. By leveraging knowledge learned from one task or domain and applying…
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[ad_1] Introduction: Differential Privacy is a promising approach for protecting sensitive data while allowing for accurate analysis and information extraction. With the increasing use of data analysis in various fields such as healthcare, finance, and…
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[ad_1] Introduction: Uncertainty quantification is a critical aspect of machine learning models that is often overlooked but can greatly impact the reliability and accuracy of predictions. By quantifying uncertainty, we can gain a better understanding…
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[ad_1] Introduction: Multimodal learning is an emerging field in machine learning that aims to combine various data sources, such as text, images, and sensors, to improve the performance of models. By fusing multiple sources of…
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[ad_1] Introduction: Active Learning is a machine learning approach that aims to efficiently label large datasets by selecting the most informative data points for manual annotation. In this thesis, we will explore the use of…
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[ad_1] Introduction: Bayesian Optimization is a powerful technique used in machine learning for hyperparameter tuning. Hyperparameter tuning is the process of choosing the best set of parameters for a machine learning algorithm to achieve optimal…
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[ad_1] Introduction: Data compression and dimensionality reduction are important techniques in the field of data management and storage. By reducing the size of data without losing critical information, these methods can help optimize storage space…
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[ad_1] Data science is a rapidly growing field that involves using statistical methods, machine learning, and other technologies to extract insights and knowledge from data. One potential area of study within data science is Monte…
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