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In the contest, operation data of a specific machine was provided to participants. We were asked to construct a machine learning model that predicts the future unusal movements of the machine. We won the special prize by constructing a high accuracy model. 
In the contest, big data of questionare with 1000 columns were provided to participants and we were asked to perform any kind of value-generating analysis freely. Our group won the first prize. This work was later published as a paper in a national conference in Japan (see the publication section). 
Published in DEIM 2019, 2019
Recommended citation: 堀賢人,鎌田麻衣子,酒井翼,早稲田風太,坂田一郎,浅谷公威 (2019) "消費者アンケートを活用した飲食店顧客の多面的理解" DEIM foram 2019, F3-4,2019 https://db-event.jpn.org/deim2019/post/papers.html
Published in IEEE EEEIC 2020, 2020
Recommended citation: Futa Waseda, Kenji Tanaka (2020). Bidding Agent for Electric Vehicles in Peer-to-Peer Electricity Trading Market considering uncertainty. EEEIC 2020.
Published in arXiv, 2022
Recommended citation: Waseda, Futa, et al. "Closer Look at the Transferability of Adversarial Examples: How They Fool Different Models Differently." arXiv preprint arXiv:2112.14337 (2021).