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TrueSkill和AdPredictor：大型机在野生环境中学习TrueSkill and AdPredictor: Large Scale Machine Learning in the Wild |
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| 课程网址: | http://videolectures.net/wapa2010_graepel_tals/ |
| 主讲教师: | Thore Graepel |
| 开课单位: | 微软公司 |
| 开课时间: | 2010-09-20 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Probabilistic Graphical Models play a crucial role in Microsoft's online services. In this talk, I will describe two powerful applications of machine learning in practice. TrueSkill is Xbox Live's Ranking and Matchmaking system and ensures that gamers online have balanced and exciting matches with equally skilled opponents. AdPredictor is the system that estimates click-through rates (CTR) for ad selection and pricing within Microsoft's search engine Bing. The two systems have in common that they are based on factor graph models and approximate Bayesian inference. They operate at a very large scale involving millions of gamers and billions of ad impressions, respectively. However, in this talk, I will put particular emphasis on those aspects of these applications that are not part of the generic machine learning setting: a) The difficulties that arise because these are closed-loop systems in which the predictions determine the future composition of the training sample. b) The consequences of the fact that these systems make decisions that have an impact on more or less rational agents (advertisers, users, gamers) with the ability to influence the training sample. Time permitting, I will show the two systems in action. This is based on joint work with Ralf Herbrich, Thomas Borchert, Tom Minka, and Joaquin Quińonero Candela. |
| 关 键 词: | 计算机科学; 机器学习; 概率图形模型 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-08：吴雨秋(课程编辑志愿者) |
| 阅读次数: | 203 |