图 书 馆
在线线性优化算法Bandit Algorithms for Online Linear Optimization |
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| 课程网址: | http://videolectures.net/icml09_cesa_bianchi_itbaolo/ |
| 主讲教师: | Nicolò Cesa-Bianchi |
| 开课单位: | 米兰大学 |
| 开课时间: | 2009-08-26 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | In the online linear optimization problem a forecaster chooses, at each time instance, a vector x from a certain given subset S of the D-dimensional Euclidean space and suffers a time-dependent loss that is linear in x. The goal of the forecaster is to achieve that, in the long run, the accumulated loss is not much larger than that of the best possible vector in S. In this talk we consider the "bandit" setting of the linear optimization problem, in which the forecaster has only access to the losses of the chosen vectors. We survey some recent algorithms that solve this problem. For the special case in which S is a subset of the d-dimensional Boolean hypercube, we describe a new forecaster whose performance, for a variety of concrete choices of S, is better than all previously known bounds, and not improvable in general. We also point out that computationally efficient implementations for various interesting choices of S exist. Joint work with Gabor Lugosi (Barcelona). |
| 关 键 词: | 非线性优化问; 线性规划优化方法; 欧氏空间 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-06：毛岱琦(课程编辑志愿者) |
| 阅读次数: | 534 |