Predicting the Winners of Borda, Kemeny and Dodgson Elections with Supervised Machine Learning (bibtex)

by Hanna Kujawska and Marija Slavkovik

Reference:

Predicting the Winners of Borda, Kemeny and Dodgson Elections with Supervised Machine Learning (Hanna Kujawska and Marija Slavkovik), In Multi-Agent Systems and Agreement Technologies - 17th European Conference, EUMAS 2020, and 7th International Conference, AT 2020, Thessaloniki, Greece, September 14-15, 2020, Revised Selected Papers (Nick Bassiliades, Georgios Chalkiadakis, Dave de Jonge, eds.), Springer, volume 12520, 2020.

Bibtex Entry:

@inproceedings{EUMAS20-a,
	author = {Hanna Kujawska and Marija Slavkovik and Jan{-}Joachim R{\"{u}}ckmann},
	bibsource = {dblp computer science bibliography, https://dblp.org},
	biburl = {https://dblp.org/rec/conf/eumas/KujawskaSR20.bib},
	booktitle = {Multi-Agent Systems and Agreement Technologies - 17th European Conference, {EUMAS} 2020, and 7th International Conference, {AT} 2020, Thessaloniki, Greece, September 14-15, 2020, Revised Selected Papers},
	doi = {10.1007/978-3-030-66412-1\_28},
	editor = {Nick Bassiliades and Georgios Chalkiadakis and Dave de Jonge},
	pages = {440--458},
	publisher = {Springer},
	series = {Lecture Notes in Computer Science},
	timestamp = {Wed, 06 Jan 2021 16:08:50 +0100},
	title = {Predicting the Winners of Borda, Kemeny and Dodgson Elections with Supervised Machine Learning},
	url = {https://doi.org/10.1007/978-3-030-66412-1\_28},
	volume = {12520},
	year = {2020},
	bdsk-url-1 = {https://doi.org/10.1007/978-3-030-66412-1%5C_28}}