PSense: Automatic Sensitivity Analysis for Probabilistic Programs

PSense: Automatic Sensitivity Analysis for Probabilistic Programs
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DOI:
10.1007/978-3-030-01090-4_23
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发表时间:
2018-10
期刊:
Proceedings of the 44th ACM SIGPLAN Symposium on Principles of Programming Languages
影响因子:
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通讯作者:
Zixin Huang;Zhenbang Wang;Sasa Misailovic
Zixin Huang;Zhenbang Wang;Sasa Misailovic
中科院分区:
其他
文献类型:
--
作者:
Zixin Huang;Zhenbang Wang;Sasa Misailovic

文献摘要

相似文献

PSense是一种新颖的概率程序灵敏度分析系统。它计算先验分布和数据参数值中的噪声对程序结果的影响。PSense使用开发人员提供的灵敏度指标将程序执行与无噪声联系起来。PSense将影响计算为每个噪声变量的一组符号函数,并支持各种非线性灵敏度指标。我们对文献中的66个项目和5个常见的灵敏度指标进行了评估,证明了PSense的有效性。
PSense is a novel system for sensitivity analysis of probabilistic programs. It computes the impact that a noise in the values of the parameters of the prior distributions and the data have on the program’s result. PSense relates the program executions with and without noise using a developer-providedsensitivity metric. PSense calculates the impact as a set of symbolic functions of each noise variable and supports various non-linear sensitivity metrics. Our evaluation on 66 programs from the literature and five common sensitivity metrics demonstrates the effectiveness of PSense.