图 书 馆
最优贝叶斯推荐集与短视最优选择查询集Optimal Bayesian Recommendation Sets and Myopically Optimal Choice Query Sets |
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| 课程网址: | http://videolectures.net/nips2010_viappiani_obr/ |
| 主讲教师: | Paolo Viappiani |
| 开课单位: | 奥尔堡大学 |
| 开课时间: | 2011-03-25 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Bayesian approaches to utility elicitation typically adopt (myopic) expected value of information (EVOI) as a natural criterion for selecting queries. However, EVOI-optimization is usually computationally prohibitive. In this paper, we examine EVOI optimization using choice queries, queries in which a user is asked to select her most preferred product from a set. We show that, under very general assumptions, the optimal choice query w.r.t.\ EVOI coincides with optimal recommendation set, that is, a set maximizing expected utility of the user selection. Since recommendation set optimization is a simpler, submodular problem, this can greatly reduce the complexity of both exact and approximate (greedy) computation of optimal choice queries. We also examine the case where user responses to choice queries are error-prone (using both constant and follow mixed multinomial logit noise models) and provide worst-case guarantees. Finally we present a local search technique that works well with large outcome spaces. |
| 关 键 词: | 贝叶斯方法; 选择查询; 推荐集优化 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-07-26：cwx |
| 阅读次数: | 31 |