矩阵积式的FPRAS逼近
FPRAS Approximation of the Matrix Permanent in Practice
摘要：
矩阵积式属于复杂性类#P-Complete。一般认为，这是计算上不可行的大规模的问题，并已完成了重要的研究近似算法的矩阵永久。我们提出了一个这样的马尔可夫链蒙特卡罗（MCMC）的实现和详细的运行时分析的完全多项式随机逼近方案（FPRAS）的矩阵永久，这以前只在理论上和大哦运行时分析。我们通过分析和实验表明，隐藏在以前的大哦分析的结果在计算上的不可行性的常数因子。
英文摘要：
The matrix permanent belongs to the complexity class #P-Complete. It is generally believed to be computationally infeasible for large problem sizes, and significant research has been done on approximation algorithms for the matrix permanent. We present an implementation and detailed runtime analysis of one such Markov Chain Monte Carlo (MCMC) based Fully Polynomial Randomized Approximation Scheme (FPRAS) for the matrix permanent, which has previously only been described theoretically and with big-Oh runtime analysis. We demonstrate by analysis and experiment that the constant factors hidden by previous big-Oh analyses result in computational infeasibility.
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