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众包预测问题的协作机制A Collaborative Mechanism for Crowdsourcing Prediction Problems |
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| 课程网址: | http://videolectures.net/nips2011_abernethy_prediction/ |
| 主讲教师: | Jacob Abernethy |
| 开课单位: | 加州大学伯克利分校 |
| 开课时间: | 2012-01-25 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Machine Learning competitions such as the Netflix Prize have proven reasonably successful as a method of “crowdsourcing” prediction tasks. But these competitions have a number of weaknesses, particularly in the incentive structure they create for the participants. We propose a new approach, called a Crowdsourced Learning Mechanism, in which participants collaboratively “learn” a hypothesis for a given prediction task. The approach draws heavily from the concept of a prediction market, where traders bet on the likelihood of a future event. In our framework, the mechanism continues to publish the current hypothesis, and participants can modify this hypothesis by wagering on an update. The critical incentive property is that a participant will profit an amount that scales according to how much her update improves performance on a released test set. |
| 关 键 词: | 机器学习竞赛; 激励结构; 预测市场 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-07-26：cwx |
| 阅读次数: | 59 |