In recent years, spectral graph sparsification techniques that can compute
ultra-sparse graph proxies have been extensively studied for accelerating
various numerical and graph-related applications. Prior nearly-linear-time
spectral sparsification methods first extract low-stretch span
我们提出了一种动态半流模型下用于计算图形谱稀疏化的首个单趟算法,该算法使用线性素描将 G 的入射矩阵维护为 O ((1/epsilon^2) n*.polylog (n)) 维,可以输出高概率下 G 的 (1+/-epsilon) 谱稀疏化。该方法利用了 G 的粗略稀疏器和 G 的入射矩阵的线性素描,通过等效电阻抽样边缘以得到任意精度的谱稀疏化。