Foundations of Deep Learning
Author:   Fengxiang He ,  Dacheng Tao
Publisher:   Springer Verlag, Singapore
Edition:   2024 ed.
ISBN:  

9789811682322


Pages:   292
Publication Date:   30 December 2024
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Foundations of Deep Learning


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Author:   Fengxiang He ,  Dacheng Tao
Publisher:   Springer Verlag, Singapore
Imprint:   Springer Verlag, Singapore
Edition:   2024 ed.
ISBN:  

9789811682322


ISBN 10:   9811682321
Pages:   292
Publication Date:   30 December 2024
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Introduction.- Background.- Conventional Statistical Learning Theory.- Difficulty of Conventional Statistical Learning Theory.- Developing Deep Learning Theory.- Generalization Bounds on Hypothesis Complexity.- Interplay of Optimization, Bayesian Inference, and Generalization.- Geometrical Properties of Loss Surface.- The Role of Over-parametrization.- Rising Concerns in Ethics and Security.- Privacy Preservation.- Fairness Protection.- Algorithmic Robustness.

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