论文阅读 [TPAMI-2022] Uniform Partitioning of Data Grid for Association Detection

论文阅读 [TPAMI-2022] Uniform Partitioning of Data Grid for Association Detection

论文搜索(studyai.com)

搜索论文: Uniform Partitioning of Data Grid for Association Detection

搜索论文: http://www.studyai.com/search/whole-site/?q=Uniform+Partitioning+of+Data+Grid+for+Association+Detection

关键字(Keywords)

Microwave integrated circuits; Mutual information; Partitioning algorithms; Heuristic algorithms; Dynamic programming; Extraterrestrial measurements; Correlation; Detection; estimation; correlation; mutual information; k-nearest neighbor

机器学习; 运筹与优化

动态规划; 最近邻

摘要(Abstract)

Inferring appropriate information from large datasets has become important.

从大型数据集中推断合适的信息变得非常重要。.

In particular, identifying relationships among variables in these datasets has far-reaching impacts.

特别是，确定这些数据集中变量之间的关系具有深远的影响。.

In this article, we introduce the uniform information coefficient (UIC), which measures the amount of dependence between two multidimensional variables and is able to detect both linear and non-linear associations.

在本文中，我们引入了统一信息系数（UIC），它测量两个多维变量之间的依赖程度，并且能够检测线性和非线性关联。.

Our proposed UIC is inspired by the maximal information coefficient (MIC) [1].; however, the MIC was originally designed to measure dependence between two one-dimensional variables.

我们提出的UIC的灵感来自最大信息系数（MIC）[1]。；然而，MIC最初设计用于测量两个一维变量之间的相关性。.

Unlike the MIC calculation that depends on the type of association between two variables, we show that the UIC calculation is less computationally expensive and more robust to the type of association between two variables.

与取决于两个变量之间关联类型的MIC计算不同，我们表明UIC计算的计算成本更低，并且对两个变量之间的关联类型更稳健。.

The UIC achieves this by replacing the dynamic programming step in the MIC calculation with a simpler technique based on the uniform partitioning of the data grid.

UIC通过将MIC计算中的动态编程步骤替换为基于数据网格均匀划分的更简单技术来实现这一点。.

This computational efficiency comes at the cost of not maximizing the information coefficient as done by the MIC algorithm.

这种计算效率的代价是没有像MIC算法那样最大化信息系数。.

We present theoretical guarantees for the performance of the UIC and a variety of experiments to demonstrate its quality in detecting associations…

我们为UIC的性能提供理论保证，并通过各种实验证明其检测关联的质量。。.

作者(Authors)

[‘Ali Mousavi’, ‘Richard G. Baraniuk’]