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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.
Bemærk: Kan ikke leveres før jul.
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.
Bemærk: Kan ikke leveres før jul.
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Decision Making Optimization Models for Business Partnerships extends non-parametric Data Envelopment Analysis (DEA) and parametric... Læs mere
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This rigorous introduction to the fundamental ideas of convexity and their use in optimization offers a unifying approach for both... Læs mere
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This book provides a broad introduction to the optimization techniques used in the design and manufacturing of epicyclic gearing.
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This book demonstrates how optimization techniques can solve hospital analytics problems. It covers advanced heuristic,... Læs mere
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The book intends to discuss the basic ideas, underlying principles, mathematical formulations, analysis and applications of the different combinatorial problems under uncertainty and attempts to provide solution/s for the same.
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With the recent advancements in machine learning (ML) and deep learning (DL), ML/DL techniques are being widely used in biomedical engineering to develop... Læs mere
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Reliability and maintenance modeling with optimization is the most fundamental and interdisciplinary research area and it can be applied to every technical and management field. This monograph provides the most recent advances and achievements in reliability and maintenance.
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The result of decades of teaching experience at a top doctoral program, this book provides a succinct and deep introduction to the theoretical foundations of... Læs mere
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