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Mendeley readers
| Chapter title |
Convex Optimization Theory
|
|---|---|
| Chapter number | 2 |
| Book title |
First-order and Stochastic Optimization Methods for Machine Learning
|
| Published by |
Springer, Cham, January 2020
|
| DOI | 10.1007/978-3-030-39568-1_2 |
| Book ISBNs |
978-3-03-039567-4, 978-3-03-039568-1
|
| Authors |
Guanghui Lan, Lan, Guanghui |
Mendeley readers
The data shown below were compiled from readership statistics for 266 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | <1% |
| Unknown | 265 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 69 | 26% |
| Student > Master | 44 | 17% |
| Researcher | 21 | 8% |
| Student > Doctoral Student | 18 | 7% |
| Student > Bachelor | 14 | 5% |
| Other | 23 | 9% |
| Unknown | 77 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 63 | 24% |
| Computer Science | 61 | 23% |
| Mathematics | 13 | 5% |
| Energy | 6 | 2% |
| Physics and Astronomy | 5 | 2% |
| Other | 32 | 12% |
| Unknown | 86 | 32% |