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Beschreibung
Machine learning techniques have become ubiquitous. We find them in our smart phones/watches, appliances, when we search the web, social networks and are even becoming mainstream in showing us personalized web content. However, little is known about the implications when two or more machine learning algorithms face each other. This textbook offers a comprehensive view of the problems faced when such algorithms share the same environment and some proposed solutions to alleviate such problems.
Social Outcomes and Strategies Impelled by Self-interests
Details
| Verlag | Scholars' Press |
| Ersterscheinung | 22. Oktober 2015 |
| Maße | 22 cm x 15 cm x 1.1 cm |
| Gewicht | 262 Gramm |
| Format | Softcover |
| ISBN-13 | 9783639763676 |
| Seiten | 164 |
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