[ad_1] Introduction: In the field of machine learning and pattern recognition, the measurement of similarity between data points is a crucial task with implications in various applications such as image retrieval, recommendation systems, and text…
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[ad_1] Introduction Representation learning has gained significant attention in the field of machine learning and artificial intelligence in recent years. It involves learning the most effective and meaningful representations of data for a given task,…
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[ad_1] Introduction: Hierarchical learning for multi-level representations is a critical aspect in the field of machine learning and artificial intelligence. It involves the development of algorithms and models that can learn hierarchical representations of data,…
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[ad_1] Introduction Online learning has become an increasingly popular method of education in recent years, with the advancement of technology making it more accessible and convenient for students. However, one of the challenges of online…
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[ad_1] Introduction Semi-supervised learning is a machine learning method that uses both labeled and unlabeled data for training purposes. In many real-world scenarios, obtaining labeled data is expensive and time-consuming, while unlabeled data is abundant.…
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[ad_1] Introduction Multi-modal learning, a subfield of machine learning, has gained significant attention in recent years due to its ability to integrate information from multiple modalities such as text, images, and audio. Cross-modal fusion, on…
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[ad_1] Introduction: Multi-task learning (MTL) has gained significant attention in the field of machine learning and artificial intelligence as it allows models to learn multiple tasks simultaneously by sharing knowledge and representations among them. One…
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[ad_1] Introduction Imitation learning, also known as behavioral cloning, is a machine learning technique that involves learning a policy from demonstrations provided by an expert. This approach is particularly useful in settings where designing a…
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[ad_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 1.9 Definition of…
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[ad_1] Introduction Meta-learning, also known as learning to learn, is a subfield of machine learning that focuses on the design and application of algorithms that can learn how to learn. The main goal of meta-learning…
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