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Bücher Englische Bücher Wissen & Bildung Naturwissenschaft, Medizin, Informatik, Technik Informatik & EDV Informatik Performance Predictor in Evolutionary Neural Architecture Search
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Performance Predictor in Evolutionary Neural Architecture Search
Nan Li, Lianbo Ma, Yuhua Qian, Bing Xue, Mengjie Zhang (Gebundene Ausgabe, Englisch)
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Beschreibung
This book explores the emerging role of performance predictors in evolutionary neural architecture search (ENAS), highlighting representative methods and practical applications that make this field both timely and impactful. By bridging performance prediction with evolutionary optimization, it addresses one of the most pressing challenges in deep learning: how to efficiently design and evaluate… neural architectures without incurring prohibitive computational costs. The book provides a systematic overview of predictor-driven approaches across diverse neural network model families, including graph neural networks, convolutional neural networks, and fuzzy neural networks. It introduces accuracy predictors as well as rank-aware predictors, illustrating how these methods enhance the efficiency, scalability, and generalizability of neural architecture search. In addition to results on widely used benchmark datasets, the book emphasizes practical applications such as defect detection and medical image segmentation, showcasing how predictor-guided ENAS delivers both research insights and real-world impact. By engaging with this book, readers will gain a clear understanding of how performance predictors accelerate ENAS, discover both classical techniques and recent advances, and appreciate the methodological and applied value of predictor-guided architecture design. The book equips its audience with frameworks to evaluate and extend predictor-based methods, positioning them at the intersection of evolutionary computation, performance prediction, and neural architecture search. Additionally, the code related to the book will be available as open source. This volume is intended for researchers, graduate students, and professionals seeking to deepen their expertise in evolutionary computation, neural networks, and neural architecture search. A foundational background in these areas will facilitate full engagement with the material and enable readers to leverage the presented concepts for both academic inquiry and applied innovation. Dieses Produkt haben wir gerade leider nicht auf Lager.
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Technische Daten
Erscheinungsdatum
21.07.2026
Sprache
Englisch
EAN
9789819591541
Herausgeber
Springer Singapore
Serien- oder Bandtitel
Genetic and Evolutionary Computation
Sonderedition
Nein
Autor
Nan Li, Lianbo Ma, Yuhua Qian, Bing Xue, Mengjie Zhang
Seitenanzahl
262
Einbandart
Gebundene Ausgabe
Buch Untertitel
Methods and Applications
Schlagwörter
Performance Predictor, Evolutionary Neural Architecture Search, Neural Architecture Search, Evolutionary Computation, Deep Learning Optimization, Accuracy Prediction, Sequence-Aware Predictors, Graph Neural Networks, Convolutional Neural Networks, Fuzzy Neural Networks, Multiobjective Optimization, Defect Detection, Uncertainty Modeling, Automated Machine Learning, Predictor-Guided Model Design
Thema-Inhalt
UYQ - Künstliche Intelligenz
PBWH - Mathematische Modellierung
Höhe
235 mm
Breite
15.5 cm
Hersteller: Springer Verlag, Singapore, Europaplatz 3,69115 Heidelberg, Germany, Heidelberg, Deutschland, ProductSafety@springernature.com, Springer Nature Customer Service Center GmbH
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