{"department":[{"_id":"34"},{"_id":"355"},{"_id":"26"}],"type":"conference","date_created":"2020-07-21T10:06:51Z","project":[{"_id":"1","name":"SFB 901"},{"name":"SFB 901 - Project Area B","_id":"3"},{"_id":"10","name":"SFB 901 - Subproject B2"},{"name":"Computing Resources Provided by the Paderborn Center for Parallel Computing","_id":"52"}],"citation":{"bibtex":"@inproceedings{Tornede_Wever_Hüllermeier_2020, title={Extreme Algorithm Selection with Dyadic Feature Representation}, booktitle={Discovery Science}, author={Tornede, Alexander and Wever, Marcel Dominik and Hüllermeier, Eyke}, year={2020} }","ama":"Tornede A, Wever MD, Hüllermeier E. Extreme Algorithm Selection with Dyadic Feature Representation. In: Discovery Science. ; 2020.","mla":"Tornede, Alexander, et al. “Extreme Algorithm Selection with Dyadic Feature Representation.” Discovery Science, 2020.","short":"A. Tornede, M.D. Wever, E. Hüllermeier, in: Discovery Science, 2020.","chicago":"Tornede, Alexander, Marcel Dominik Wever, and Eyke Hüllermeier. “Extreme Algorithm Selection with Dyadic Feature Representation.” In Discovery Science, 2020.","ieee":"A. Tornede, M. D. Wever, and E. Hüllermeier, “Extreme Algorithm Selection with Dyadic Feature Representation,” presented at the Discovery Science 2020, 2020.","apa":"Tornede, A., Wever, M. D., & Hüllermeier, E. (2020). Extreme Algorithm Selection with Dyadic Feature Representation. Discovery Science. Discovery Science 2020."},"publication":"Discovery Science","user_id":"5786","language":[{"iso":"eng"}],"_id":"17407","date_updated":"2022-01-06T06:53:10Z","conference":{"name":"Discovery Science 2020"},"author":[{"first_name":"Alexander","last_name":"Tornede","full_name":"Tornede, Alexander","id":"38209"},{"full_name":"Wever, Marcel Dominik","last_name":"Wever","first_name":"Marcel Dominik","orcid":" https://orcid.org/0000-0001-9782-6818","id":"33176"},{"id":"48129","first_name":"Eyke","last_name":"Hüllermeier","full_name":"Hüllermeier, Eyke"}],"status":"public","year":"2020","title":"Extreme Algorithm Selection with Dyadic Feature Representation"}