Approximating the Permanent of a Random Matrix with Vanishing Mean

@article{Eldar2018ApproximatingTP,
  title={Approximating the Permanent of a Random Matrix with Vanishing Mean},
  author={Lior Eldar and S. Mehraban},
  journal={2018 IEEE 59th Annual Symposium on Foundations of Computer Science (FOCS)},
  year={2018},
  pages={23-34}
}
  • Lior Eldar, S. Mehraban
  • Published 2018
  • Mathematics, Computer Science, Physics
  • 2018 IEEE 59th Annual Symposium on Foundations of Computer Science (FOCS)
The permanent is #P-hard to compute exactly on average for natural random matrices including matrices over finite fields or Gaussian ensembles. Should we expect that it remains #P-hard to compute on average if we only care about approximation instead of exact computation? In this work we take a first step towards resolving this question: We present a quasi-polynomial time deterministic algorithm for approximating the permanent of a typical n × n random matrix with unit variance and vanishing… Expand
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