• Computer Science, Mathematics
  • Published in NeurIPS 2019

Approximating the Permanent by Sampling from Adaptive Partitions

@article{Kuck2019ApproximatingTP,
  title={Approximating the Permanent by Sampling from Adaptive Partitions},
  author={Jonathan Kuck and Tri Dao and Hamid Rezatofighi and Ashish Sabharwal and Stefano Ermon},
  journal={ArXiv},
  year={2019},
  volume={abs/1911.11856}
}
Computing the permanent of a non-negative matrix is a core problem with practical applications ranging from target tracking to statistical thermodynamics. However, this problem is also #P-complete, which leaves little hope for finding an exact solution that can be computed efficiently. While the problem admits a fully polynomial randomized approximation scheme, this method has seen little use because it is both inefficient in practice and difficult to implement. We present ADAPART, a simple and… CONTINUE READING

Figures, Tables, and Topics from this paper.

Explore Further: Topics Discussed in This Paper