图 书 馆
条件抽样下更快的测试算法Faster Algorithms for Testing under Conditional Sampling |
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| 课程网址: | https://videolectures.net/videos/colt2015_suresh_conditional_samp... |
| 主讲教师: | Ananda Theertha Suresh |
| 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: | There has been considerable recent interest in distribution-tests whose run-time and sample requirements are sublinear in the domain-size $k$. We study two of the most important tests under the conditional-sampling model where each query specifies a subset $S$ of the domain, and the response is a sample drawn from $S$ according to the underlying distribution. For identity testing, which asks whether the underlying distribution equals a specific given distribution or $\delta$-differs from it, we reduce the known time and sample complexities from $O(\delta^{-4})$ to $O(\delta^{-2})$, thereby matching the information theoretic lower bound. For closeness testing, which asks whether two distributions underlying observed data sets are equal or different, we reduce existing complexity from $O(\delta^{-4} \log^5 k)$ to an even sub-logarithmic $O(\delta^{-5} \log \log k)$, and providing a better bound to an open problem in Bertinoro Workshop on Sublinear Algorithms. |
| 关 键 词: | 次线性; 条件抽样模型; 底层分布 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2025-03-31：zsp |
| 最后编审: | 2025-03-31：zsp |
| 阅读次数: | 2 |