图 书 馆
带状线性优化的复杂性On the Complexity of Bandit Linear Optimization |
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| 课程网址: | https://videolectures.net/videos/colt2015_shamir_linear_optimizat... |
| 主讲教师: | Ohad Shamir |
| 开课单位: | 信息不详。欢迎您在右侧留言补充。 |
| 开课时间: | 2025-02-04 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We study the attainable regret for online linear optimization problems with bandit feedback, where unlike the full-information setting, the player can only observe its own loss rather than the full loss vector. We show that the price of bandit information in this setting can be as large as $d$, disproving the well-known conjecture (\cite{dani2007price}) that the regret for bandit linear optimization is at most $\sqrt{d}$ times the full-information regret. Surprisingly, this is shown using ``trivial'' modifications of standard domains, which have no effect in the full-information setting. This and other results we present highlight some interesting differences between full-information and bandit learning, which were not considered in previous literature. |
| 关 键 词: | 线性优化; 损失向量; 强盗学习 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2025-03-27：zsp |
| 最后编审: | 2025-03-28：liyy |
| 阅读次数: | 5 |