Swiss-Chocolate: Combining Flipout Regularization and Random Forests with Artificially Built Subsystems to Boost Text-Classification for Sentiment
Fatih Uzdilli, Martin Jaggi, Dominic Egger, Pascal Julmy, Leon Derczynski, Mark Cieliebak
- Anthology ID:
- S15-2101
- Volume:
- Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)
- Month:
- June
- Year:
- 2015
- Address:
- Denver, Colorado
- Editors:
- Preslav Nakov, Torsten Zesch, Daniel Cer, David Jurgens
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 608–612
- Language:
- URL:
- https://aclanthology.org/S15-2101
- DOI:
- 10.18653/v1/S15-2101
- Cite (ACL):
- Fatih Uzdilli, Martin Jaggi, Dominic Egger, Pascal Julmy, Leon Derczynski, and Mark Cieliebak. 2015. Swiss-Chocolate: Combining Flipout Regularization and Random Forests with Artificially Built Subsystems to Boost Text-Classification for Sentiment. In Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015), pages 608–612, Denver, Colorado. Association for Computational Linguistics.
- Cite (Informal):
- Swiss-Chocolate: Combining Flipout Regularization and Random Forests with Artificially Built Subsystems to Boost Text-Classification for Sentiment (Uzdilli et al., SemEval 2015)
- PDF:
- https://preview.aclanthology.org/dois-2013-emnlp/S15-2101.pdf