Cyber Security Cryptography and Machine Learning
Springer International Publishing
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
Mendeley readers
| Chapter title |
Programmable Bootstrapping Enables Efficient Homomorphic Inference of Deep Neural Networks
|
|---|---|
| Book title |
Cyber Security Cryptography and Machine Learning
|
| Published by |
Springer, Cham, July 2021
|
| DOI | 10.1007/978-3-030-78086-9_1 |
| Book ISBNs |
978-3-03-078085-2, 978-3-03-078086-9
|
| Authors |
Ilaria Chillotti, Marc Joye, Pascal Paillier, Chillotti, Ilaria, Joye, Marc, Paillier, Pascal |
Mendeley readers
The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 51 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 18% |
| Student > Master | 5 | 10% |
| Researcher | 4 | 8% |
| Other | 3 | 6% |
| Student > Bachelor | 2 | 4% |
| Other | 3 | 6% |
| Unknown | 25 | 49% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 16 | 31% |
| Engineering | 6 | 12% |
| Mathematics | 1 | 2% |
| Physics and Astronomy | 1 | 2% |
| Unspecified | 1 | 2% |
| Other | 0 | 0% |
| Unknown | 26 | 51% |