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Titlebook: Learning and Decision-Making from Rank Data; Lirong Xia Book 2019 Springer Nature Switzerland AG 2019

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31#
發(fā)表于 2025-3-26 21:29:45 | 只看該作者
32#
發(fā)表于 2025-3-27 01:35:05 | 只看該作者
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發(fā)表于 2025-3-27 08:52:31 | 只看該作者
Mixture Models for Rank Data,ty for each group. This can be achieved by first clustering the agents according to their preferences over the activities, and then learn the common preferences for each group to recommend an activity.
34#
發(fā)表于 2025-3-27 12:00:16 | 只看該作者
Socially Desirable Group Decision-Making from Rank Data,Scenario 1 in Chapter 1), fairness is a fundamental to democracy. In the group activity selection problem (Scenario 3 in Chapter 1), it is important to guarantee that the partition and activity selection are done in a fair way.
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發(fā)表于 2025-3-27 13:42:45 | 只看該作者
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發(fā)表于 2025-3-27 21:40:05 | 只看該作者
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發(fā)表于 2025-3-28 04:02:01 | 只看該作者
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發(fā)表于 2025-3-28 06:26:08 | 只看該作者
-world problems. We then examined the trajectories and the impact of pedagogical innovations that were designed for the Singapore mathematics classrooms and that sought to address the trade-offs. From a postulation of factors behind the challenges of implementing and sustaining these innovations in
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