[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 In today’s rapidly changing world, the ability to continuously adapt and learn throughout one’s lifetime has become increasingly important. Lifelong learning is the process of acquiring new knowledge, skills, and abilities to stay…
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[ad_1] Introduction Artificial Intelligence (AI) has become an integral part of our daily lives, influencing decision making in various sectors such as healthcare, finance, and criminal justice. However, concerns have been raised about the potential…
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[ad_1] Introduction Self-supervised learning has emerged as a promising technique in the field of machine learning, especially for tasks where labeled data is scarce or expensive to obtain. This approach aims to leverage the inherent…
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[ad_1] Introduction Zero-shot learning is a promising technique in machine learning, where the model is trained on a set of classes but is able to generalize to unseen classes at test time. This approach is…
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[ad_1] Introduction: Few-shot learning is a crucial area of research in machine learning, particularly in scenarios where the amount of available data is limited. In such cases, traditional machine learning algorithms may struggle to generalize…
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[ad_1] Introduction Reinforcement learning is a subfield of machine learning that focuses on enabling agents to make sequential decisions in order to maximize rewards. It has gained significant attention in recent years due to its…
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[ad_1] Introduction Evolutionary computation is a powerful optimization technique inspired by the process of natural selection. This method involves generating potential solutions to a problem and then using genetic operators such as mutation, crossover, and…
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[ad_1] Introduction Cognitive computing is a cutting-edge technology that combines artificial intelligence, machine learning, and natural language processing to create intelligent systems capable of understanding, reasoning, and learning from data. These systems are designed to…
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[ad_1] ***Thesis Title: Affective Computing for Emotion Recognition*** **Chapter 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…
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