Efficient mechanisms for peer grading and dueling bandits
學年 107
學期 1
發表日期 2018-11-14
作品名稱 Efficient mechanisms for peer grading and dueling bandits
作品名稱（其他語言）
著者 Chuang-Chieh Lin; Chi-Jen Lu
作品所屬單位
出版者
會議名稱 The 10th Asian Conference on Machine Learning (ACML)
會議地點 Beijing, China
摘要 Many scenarios in our daily life require us to infer some ranking over items or people based on limited information. In this paper, we consider two such scenarios, one for ranking student papers in massive online open courses and one for identifying the best player (or team) in sports tournaments. For the peer grading problem, we design a mechanism with a new way of matching graders to papers. This allows us to aggregate partial rankings from graders into a global one, with an accuracy rate matching the best in previous works, but with a much simpler analysis. For the winner selection problem in sports tournaments, we cast it as the well-known dueling bandit problem and identify a new measure to minimize: the number of parallel rounds, as one normally would not like a large tournament to last too long. We provide mechanisms which can determine the optimal or an almost optimal player in a small number of parallel rounds and at the same time using a small number of competitions.
關鍵字 Ordinal peer-grading;dueling bandits;Borda count
語言 en_US
收錄於
會議性質 國際
校內研討會地點 無
研討會時間 20181114~20181116
通訊作者 Chi-Jen Lu
國別 CHN
公開徵稿
出版型式
出處 Proceedings of Machine Learning Research (PMLR) 95, p. 740-755
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/120098 )

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