图 书 馆
在线学习，遗憾最小化和博弈论Online Learning, Regret Minimization, and Game Theory |
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| 课程网址: | http://videolectures.net/mlss08au_blum_org/ |
| 主讲教师: | Avrim Blum |
| 开课单位: | 卡内基梅隆大学 |
| 开课时间: | 2008-05-07 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | The first part of tha tutorial will discuss adaptive algorithms for making decisions in uncertain environments (e.g., what route should I take to work if I have to decide before I know what traffic will like today?) and connections to central concepts in game theory (e.g., what can we say about how traffic will behave overall if everyone is adapting their behavior in such a way?). He will discuss the notions of external and internal regret, algorithms for "combining expert advice" and "sleeping experts" problems, algorithms for implicitly specified problems, and connections to game-theoretic notions of Nash and correlated equilibria. The second part of tha tutorial will be about some recent work on learning with similarity functions that are not necessarily legal kernels. The high-level question here is: if you have a measure of similarity between data points, how closely related does it have to be to your classification problem in order to be useful for learning? |
| 关 键 词: | 自适应算法; 博弈论; 相似性度量 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-22：chenxin |
| 阅读次数: | 204 |