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Clique Matrices for Statistical Graph Decomposition and Parameterising Restricted Positive Definite Matrices

机译:统计图分解和参数化约束正定矩阵的集团矩阵

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We introduce Clique Matrices as an alternative representation of undirected graphs, being a generalisation of the incidence matrix representation. Here we use clique matrices to decompose a graph into a set of possibly overlapping clusters, defined as well-connected subsets of vertices. The decomposition is based on a statistical description which encourages clusters to be well connected and few in number. Inference is carried out using a variational approximation. Clique matrices also play a natural role in parameterising positive definite matrices under zero constraints on elements of the matrix. We show that clique matrices can parame-terise all positive definite matrices restricted according to a decomposable graph and form a structured Factor Analysis approximation in the non-decomposable case.
机译:我们引入Clique矩阵作为无向图的替代表示,是对入射矩阵表示的概括。在这里,我们使用集团矩阵将图分解为一组可能重叠的簇,这些簇定义为顶点的连接良好的子集。分解基于统计描述,该描述鼓励群集连接良好且数量很少。使用变分近似进行推断。在对矩阵元素的零约束下,参数化矩阵在参数化正定矩阵中也起着自然作用。我们表明,集团矩阵可以参数化根据可分解图限制的所有正定矩阵,并在不可分解的情况下形成结构化因子分析近似。

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