New Trends in Disruptive Technologies, Tech Ethics and Artificial Intelligence
Springer International Publishing
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X Demographics
Mendeley readers
| Chapter title |
One-vs.-One Mitigation of Intersectional Bias: A General Method for Extending Fairness-Aware Binary Classification
|
|---|---|
| Book title |
New Trends in Disruptive Technologies, Tech Ethics and Artificial Intelligence
|
| Published by |
Springer, Cham, October 2021
|
| DOI | 10.1007/978-3-030-87687-6_5 |
| Book ISBNs |
978-3-03-087686-9, 978-3-03-087687-6
|
| Authors |
Kobayashi, Kenji, Nakao, Yuri |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 2 | 67% |
| United Kingdom | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 15 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 20% |
| Student > Doctoral Student | 3 | 20% |
| Student > Master | 2 | 13% |
| Student > Bachelor | 1 | 7% |
| Other | 1 | 7% |
| Other | 1 | 7% |
| Unknown | 4 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 8 | 53% |
| Economics, Econometrics and Finance | 1 | 7% |
| Social Sciences | 1 | 7% |
| Engineering | 1 | 7% |
| Unknown | 4 | 27% |