Decoding From Pooled Data: Phase Transitions of Message Passing

@article{Alaoui2019DecodingFP,
  title={Decoding From Pooled Data: Phase Transitions of Message Passing},
  author={A. El Alaoui and Aaditya Ramdas and F. Krzakala and L. Zdeborov{\'a} and Michael I. Jordan},
  journal={IEEE Transactions on Information Theory},
  year={2019},
  volume={65},
  pages={572-585}
}
  • A. El Alaoui, Aaditya Ramdas, +2 authors Michael I. Jordan
  • Published 2019
  • Computer Science, Mathematics
  • IEEE Transactions on Information Theory
  • We consider the problem of decoding a discrete signal of categorical variables from the observation of several histograms of pooled subsets of it. We present an approximate message passing (AMP) algorithm for recovering the signal in the <italic>random dense</italic> setting where each observed histogram involves a random subset of entries of size proportional to <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula>. We characterize the performance of the algorithm in the… CONTINUE READING

    Figures and Topics from this paper.

    Citations

    Publications citing this paper.
    SHOWING 1-4 OF 4 CITATIONS

    Decoding from pooled data: Phase transitions of message passing

    VIEW 1 EXCERPT
    CITES BACKGROUND

    Quantitative Group Testing in the Sublinear Regime

    VIEW 9 EXCERPTS
    CITES BACKGROUND & METHODS
    HIGHLY INFLUENCED

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 14 REFERENCES

    Randomly spread CDMA: asymptotics via statistical physics

    VIEW 1 EXCERPT

    Universality in polytope phase transitions and iterative algorithms

    VIEW 2 EXCERPTS

    Message-passing algorithms for compressed sensing

    Statistical physics of inference: thresholds and algorithms

    VIEW 1 EXCERPT

    Data extraction via histogram and arithmetic mean queries: Fundamental limits and algorithms