Region-Based Active Learning with Hierarchical and Adaptive Region Construction
Learning of classification models in practice often relies on human annotation effort in which humans assign class labels to data instances. As this process can be very time-consuming and costly, finding effective ways to reduce the annotation cost becomes critical for building such models. To solve...
Uložené v:
| Vydané v: | Proceedings of the ... SIAM International Conference on Data Mining Ročník 2019; s. 441 |
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| Hlavní autori: | , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
United States
01.05.2019
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| ISSN: | 2167-0102 |
| On-line prístup: | Zistit podrobnosti o prístupe |
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