Energy efficiency and robustness of advanced machine learning architectures a cross-layer approach / Alberto Marchisio, Muhammad Shafique.
| Author/creator | Marchisio, Alberto |
| Other author | Shafique, Muhammad. |
| Format | Electronic |
| Publication Info | Boca Raton : CRC Press, Taylor & Francis Group, 2025. |
| Description | xiv, 346 pages : illustrations ; 24 cm. |
| Supplemental Content | Full text available from Taylor & Francis eBooks |
| Subjects |
| Series | Chapman & Hall/CRC artificial intelligence and robotics series |
| Contents | Hardware and software optimizations for capsule networks -- Adversarial security threats for DNNs and CapsNets -- Inetration and of multiple and design objectives into NAS frameworks for CapsNets and DNNs -- Efficient optimizations for spiking neural networks on neuromorphic hardware -- Security threats for SNNs on discrete and event-based data. |
| Abstract | "Machine Learning (ML) algorithms have shown a high level of accuracy, and applications are widely used in many systems and platforms. However, developing efficient ML-based systems requires addressing three problems: energy-efficiency, robustness, and techniques that typically focus on optimizing for a single objective/have a limited set of goals"-- Provided by publisher. |
| Bibliography note | Includes bibliographical references and index. |
| Access restriction | Available only to authorized users. |
| Technical details | Mode of access: World Wide Web |
| Genre/form | Electronic books. |
| LCCN | 2024023579 |
| ISBN | 9781032855509 (hardback) |
| ISBN | 9781032870137 (paperback) |
| ISBN | (ebook) |
Availability
| Library | Location | Call Number | Status | Item Actions |
|---|---|---|---|---|
| Electronic Resources | Access Content Online | ✔ Available |