Sequential Monte Carlo for counting vertex covers in general graphs
نویسندگان
چکیده
In this paper we describe a Sequential Importance Sampling (SIS) procedure for counting the number of vertex covers in general graphs. The optimal SIS proposal distribution is the uniform over a suitably restricted set, but is not implementable. We will consider two proposal distributions as approximations to the optimal. Both proposals are based on randomization techniques. The first randomization is the classic probability model of random graphs, and in fact, the resulting SIS algorithm shows polynomial
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عنوان ژورنال:
- Statistics and Computing
دوره 26 شماره
صفحات -
تاریخ انتشار 2016