论文标题
F-IVM：学习快速发展的关系数据
F-IVM: Learning over Fast-Evolving Relational Data
论文作者
论文摘要
F-IVM是一个用于实时分析的系统，例如通过快速发展的关系数据库定义的培训数据集对机器学习应用程序。我们将展示三种此类应用的F-IVM：模型选择，Chow-Liu树和脊线性回归。
F-IVM is a system for real-time analytics such as machine learning applications over training datasets defined by queries over fast-evolving relational databases. We will demonstrate F-IVM for three such applications: model selection, Chow-Liu trees, and ridge linear regression.
