论文标题
测试异常：主动策略和非反应分析
Testing for Anomalies: Active Strategies and Non-asymptotic Analysis
论文作者
论文摘要
验证多组分系统是否存在异常的问题。随着时间的推移，每个组件都可以以数据驱动的方式进行探测，以获得嘈杂的观测值，以指示所选组件是否是异常的。目的是最大程度地减少错误地宣布该系统无异常的可能性，同时确保正确宣布其安全的概率足够大。该问题被建模为Neyman-Pearson设置中的主动假设检验问题。组件选择和推理策略是在非反应方案中设计和分析的。对于特定类别的同质问题，提供了更强的（相对于先前的工作）非反应性匡威和可实现性界限。
The problem of verifying whether a multi-component system has anomalies or not is addressed. Each component can be probed over time in a data-driven manner to obtain noisy observations that indicate whether the selected component is anomalous or not. The aim is to minimize the probability of incorrectly declaring the system to be free of anomalies while ensuring that the probability of correctly declaring it to be safe is sufficiently large. This problem is modeled as an active hypothesis testing problem in the Neyman-Pearson setting. Component-selection and inference strategies are designed and analyzed in the non-asymptotic regime. For a specific class of homogeneous problems, stronger (with respect to prior work) non-asymptotic converse and achievability bounds are provided.
