Machine Learning Safety
Machine learning algorithms allow computers to learn without being explicitly programmed. Their application is now spreading to highly sophisticated tasks across multiple domains, such as medical diagnostics or fully autonomous vehicles. While this development holds great potential, it also raises n...
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| Main Authors: | , , |
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| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | inglés |
| Publicado: |
Singapore :
Springer Nature Singapore : Imprint: Springer,
2023.
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| Edición: | 1st ed. 2023. |
| Series: | Artificial Intelligence: Foundations, Theory, and Algorithms,
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| Subjects: | |
| Acceso en liña: | https://doi.org/10.1007/978-981-19-6814-3 |
| Tags: |
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Table of Contents:
- 1. Introduction
- 2. Safety of Simple Machine Learning Models
- 3. Safety of Deep Learning
- 4. Robustness Verification of Deep Learning
- 5. Enhancement to Robustness and Generalization
- 6. Probabilistic Graph Model
- A. Mathematical Foundations
- B. Competitions.