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Dec, 2019
异质Thurstone偏好模型在排名聚合中的应用
Rank Aggregation via Heterogeneous Thurstone Preference Models
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Tao Jin, Pan Xu, Quanquan Gu, Farzad Farnoud
TL;DR
提议使用异构Thurstone模型（HTM）聚合排名数据，并提出一种基于交替梯度下降的排名聚合算法，能够同时估计不同用户的基础物品得分和准确度水平。理论上证明该算法的收敛速度线性，且表现优于现有方法。
Abstract
We propose the
heterogeneous thurstone model
(HTM) for aggregating
ranked data
, which can take the accuracy levels of different users into account. By allowing different
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