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随机游走扰动预测

Prediction by random-walk perturbation
课程网址: http://videolectures.net/colt2013_neu_prediction/  
主讲教师: Gergely Neu
开课单位: INRIA研究机构
开课时间: 2013-08-09
课程语种: 英语
中文简介:
我们提出了一个遵循扰动的领导者在线预测算法的版本,其中累积损失被独立的对称随机游走扰动。预测器显示出对最佳阶数O(√nlogN)的预期遗憾,其中n是时间范围,N是专家的数量。更重要的是,它表明预报员在预期中最多改变其预测O(√nlogN)次。我们还将分析扩展到在线组合优化,并表明即使在这种更一般的设置中,预报员很少在专家之间切换,同时对近乎最优的顺序感到遗憾。
课程简介: We propose a version of the follow-the-perturbed-leader online prediction algorithm in which the cumulative losses are perturbed by independent symmetric random walks. The forecaster is shown to achieve an expected regret of the optimal order O(√nlogN) where n is the time horizon and N is the number of experts. More importantly, it is shown that the forecaster changes its prediction at most O(√nlogN) times, in expectation. We also extend the analysis to online combinatorial optimization and show that even in this more general setting, the forecaster rarely switches between experts while having a regret of near-optimal order.
关 键 词: 线预测算法; 线组合优化
课程来源: 视频讲座网
最后编审: 2020-07-29:yumf
阅读次数: 59