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Machine learning with quantum computers / / Maria Schuld, Francesco Petruccione
| Machine learning with quantum computers / / Maria Schuld, Francesco Petruccione |
| Autore | Schuld Maria |
| Edizione | [Second edition.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (321 pages) |
| Disciplina | 004.1 |
| Collana | Quantum science and technology |
| Soggetto topico | Quantum computers |
| ISBN | 3-030-83098-5 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996466842903316 |
Schuld Maria
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| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Machine Learning with Quantum Computers / / by Maria Schuld, Francesco Petruccione
| Machine Learning with Quantum Computers / / by Maria Schuld, Francesco Petruccione |
| Autore | Schuld Maria |
| Edizione | [2nd ed. 2021.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 |
| Descrizione fisica | 1 online resource (321 pages) |
| Disciplina | 004.1 |
| Collana | Quantum Science and Technology |
| Soggetto topico |
Quantum computers
Machine learning Mathematics Quantum Computing Machine Learning Mathematics and Computing |
| ISBN | 3-030-83098-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Introduction -- Chapter 2. Machine Learning -- Chapter 3. Quantum Computing -- Chapter 4. Representing Data on a Quantum Computer -- Chapter 5. Variational Circuits as Machine Learning Models -- Chapter 6. Quantum Models as Kernel Methods -- Chapter 7. Fault-Tolerant Quantum Machine Learning -- Chapter 8. Approaches Based on the Ising Model -- Chapter 9. Potential Quantum Advantages. |
| Record Nr. | UNINA-9910506399603321 |
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Schuld Maria
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Supervised Learning with Quantum Computers / / by Maria Schuld, Francesco Petruccione
| Supervised Learning with Quantum Computers / / by Maria Schuld, Francesco Petruccione |
| Autore | Schuld Maria |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (293 pages) |
| Disciplina | 530.1201514 |
| Collana | Quantum Science and Technology |
| Soggetto topico |
Quantum theory
Quantum computers Pattern recognition systems Spintronics Mathematical physics Artificial intelligence Quantum Physics Quantum Computing Automated Pattern Recognition Theoretical, Mathematical and Computational Physics Artificial Intelligence |
| ISBN | 3-319-96424-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Background -- How quantum computers can classify data -- Organisation of the book -- Machine Learning -- Prediction -- Models -- Training -- Methods in machine learning -- Quantum Information -- Introduction to quantum theory -- Introduction to quantum computing -- An example: The Deutsch-Josza algorithm -- Strategies of information encoding -- Important quantum routines -- Quantum advantages -- Computational complexity of learning -- Sample complexity -- Model complexity -- Information encoding -- Basis encoding -- Amplitude encoding -- Qsample encoding -- Hamiltonian encoding -- Quantum computing for inference -- Linear models -- Kernel methods -- Probabilistic models -- Quantum computing for training -- Quantum blas -- Search and amplitude amplification -- Hybrid training for variational algorithms -- Quantum adiabatic machine learning -- Learning with quantum models -- Quantum extensions of Ising-type models -- Variational classifiers and neural networks -- Other approaches to buildquantum models -- Prospects for near-term quantum machine learning -- Small versus big data -- Hybrid versus fully coherent approaches -- Qualitative versus quantitative advantages -- What machine learning can do for quantum computing -- References. |
| Record Nr. | UNINA-9910300533803321 |
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Schuld Maria
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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