使用模拟辅助机器学习质量保证过程的智能用户界面的设计和优化（CS）

在现实世界中，机器学习（ML）的许多关键任务型的应用程序都需要进行质量保证（QA）流程，然后才能部署ML模型的决策或预测。由于QA4ML用户必须查看大量数据并执行许多输入操作来纠正ML模型所产生的错误，因此，经过优化设计的用户界面（UI）可以显着降低交互成本。UI的有效性可能受许多因素影响，例如，同一时间处理的数据对象的数量，用于纠正错误的命令的类型以及用作协助用户的算法的可行性。我们建议使用模拟的方式来辅助QA4ML流程的智能用户界面的设计和优化。特别是，我们专注于在选择合适的命令和算法时模拟人类智能的综合效果，在提供通用算法集合以对要保证质量的数据对象进行重新排序时，机器智能会提供模拟。

原文题目：Using Simulation to Aid the Design and Optimization of Intelligent User Interfaces for Quality Assurance Processes in Machine Learning

原文：Many mission-critical applications of machine learning (ML) in the real-world require a quality assurance (QA) process before the decisions or predictions of an ML model can be deployed. Because QA4ML users have to view a non-trivial amount of data and perform many input actions to correct errors made by the ML model, an optimally-designed user interface (UI) can reduce the cost of interactions significantly. A UI's effectiveness can be affected by many factors, such as the number of data objects processed concurrently, the types of commands for correcting errors, and the availability of algorithms for assisting users. We propose using simulation to aid the design and optimization of intelligent user interfaces for QA4ML processes. In particular, we focus on simulating the combined effects of human intelligence in selecting appropriate commands and algorithms, and machine intelligence in providing a collection of general-purpose algorithms for reordering data objects to be quality-assured.