Liu Peng

Deep Learning Generalization

Theoretical Foundations and Practical Strategies

• Broschiertes Buch

Produktbeschreibung

This book provides a comprehensive exploration of generalization in deep learning, focusing on both theoretical foundations and practical strategies. It delves deeply into how machine learning models, particularly deep neural networks, achieve robust performance on unseen data.

---

Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.

Produktdetails

• Verlag: Taylor & Francis Ltd
• Seitenzahl: 200
• Erscheinungstermin: 27. Juni 2025
• Englisch
• Abmessung: 234mm x 156mm
• ISBN-13: 9781032841892
• ISBN-10: 1032841893
• Artikelnr.: 72543290

Autorenporträt

Liu Peng is currently an Assistant Professor of Quantitative Finance at the Singapore Management University (SMU). His research interests include generalization in deep learning, sparse estimation, Bayesian optimization.

Inhaltsangabe

1. Unveiling Generalization in Deep Learning 2. Introduction to Statistical
Learning Theory 3. Classical Perspectives on Generalization 4. Modern
Perspectives on Generalization 5. Fundamentals of Deep Neural Networks 6. A
Concluding Perspective