2.035 hasil untuk machine learning
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Federated Learning
Federated Learning (FL) represents a transformative leap in distributed machine learning by enabling multiple clients to collaboratively solve complex tasks without compromising data privacy. This innovative approach eliminates the need for centralized cloud storage, ensuring privacy-preserving…
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Transfer Learning
This edited volume explores the potential of transfer learning in advancing artificial intelligence (AI) across diverse domains. Transfer learning enables AI systems to leverage knowledge gained from one task to enhance performance in another, significantly reducing data requirements and training…
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Advances and Applications in Deep Learning
…of AI is notoriously changing the world we live in. In this context, Deep Learning (DL) is one of the techniques that has taken the lead for cognitive processes, pattern recognition, object detection, and machine learning, all of which have played a crucial role in the growth of AI. As such, this…
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Efficient Reinforcement Learning using Gaussian Processes
This book examines Gaussian processes in both model-based reinforcement learning (RL) and inference in nonlinear dynamic systems.First, we introduce PILCO, a fully Bayesian approach for efficient RL in continuous-valued state and action spaces when no expert knowledge is available. PILCO takes…
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Representation Learning for Natural Language Processing
This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including…
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Chapter 6 Learning to Discriminate
…recidivism. A similar approach could be taken to the design of newer, machine learning-based (ML) tools for predicting recidivism: information about race could be withheld from the ML tool during its training phase, ensuring that the resulting predictive model does not use race as an explicit…
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Advanced Learning Analytics Methods
This is an open access book. This comprehensive and timely methodological book introduces several novel topics under the overarching sections of advanced learning analytics (LA), artificial intelligence (AI), precision education, and complex systems. These topics are presented using accessible…
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Handbook of Personalized Learning
The Handbook of Personalized Learning offers a theoretically grounded conceptualization for the development and implementation of personalizing learning. This comprehensive volume addresses personalized learning’s roots in educational, cognitive, and social psychological studies of learning as well…
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Future Speech Interfaces with Sensors and Machine Intelligence
…in noisy conditions; and the difficulty of creating complex man–machine interfaces. The Special Issue “Future Speech Interfaces with Sensors and Machine Intelligence” assembles eleven contributions that cover multimodal and silent speech interfaces; lip reading applications; novel sensors for…
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Deep Learning in Medical Image Analysis
The accelerating power of deep learning in diagnosing diseases will empower physicians and speed up decision making in clinical environments. Applications of modern medical instruments and digitalization of medical care have generated enormous amounts of medical images in recent years. In this big…
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Information Theory and Its Application in Machine Condition Monitoring
…an exponential increase of demand is leading an increasing requirement of machine output. As a result, in most modern industries, machines have to work for 24 hours a day. All these factors are leading to the deterioration of machine health in a higher rate than before. Breakdown of the key…
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Learning Analytics Methods and Tutorials
This open access comprehensive methodological book offers a much-needed answer to the lack of resources and methodological guidance in learning analytics, which has been a problem ever since the field started. The book covers all important quantitative topics in education at large as well as the…
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Chapter Deep Multiagent Reinforcement Learning Methods Addressing the Scalability Challenge
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Deep Learning Architecture and Applications
As one of the fastest-growing topics in machine learning, deep learning algorithms have achieved unprecedented success in recent years. Novel paradigms (such as contrastive learning and few-shot learning) in deep learning and rising neural network architectures (e.g., transformer and masked…
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Deep Learning for Toxicity and Disease Prediction
This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from…
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Deep Learning-Based Action Recognition
…pattern includes the processing technology of human behavior data for learning, technology of expressing feature values of images, technology of extracting spatiotemporal information of images, technology of recognizing human posture, and technology of gesture recognition. Research on these…
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Chapter Risk Assessment and Automated Anomaly Detection Using a Deep Learning Architecture
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Juga tersedia di: DOAB
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Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection
…reference resource for researchers and designers in the field of robot learning and multimodal perception, as well as for senior undergraduate and graduate university students.
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A Gentle Introduction to Data, Learning, and Model Order Reduction
This open access book explores the latest advancements in simulation performance, driven by model order reduction, informed and augmented machine learning technologies and their combination into the so-called hybrid digital twins. It provides a comprehensive review of three key frameworks shaping…
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