# Sample complexity of population recovery

@article{Polyanskiy2017SampleCO, title={Sample complexity of population recovery}, author={Yury Polyanskiy and Ananda Theertha Suresh and Yihong Wu}, journal={ArXiv}, year={2017}, volume={abs/1702.05574} }

The problem of population recovery refers to estimating a distribution based on incomplete or corrupted samples. Consider a random poll of sample size $n$ conducted on a population of individuals, where each pollee is asked to answer $d$ binary questions. We consider one of the two polling impediments: (a) in lossy population recovery, a pollee may skip each question with probability $\epsilon$; (b) in noisy population recovery, a pollee may lie on each question with probability $\epsilon… CONTINUE READING

#### Paper Mentions

BLOG POST

#### Citations

##### Publications citing this paper.

SHOWING 1-10 OF 10 CITATIONS

## Extrapolating the profile of a finite population

VIEW 2 EXCERPTS

CITES BACKGROUND

## Sharp bounds for population recovery

VIEW 9 EXCERPTS

CITES RESULTS & METHODS

HIGHLY INFLUENCED

## Statistical Windows in Testing for the Initial Distribution of a Reversible Markov Chain

VIEW 1 EXCERPT

CITES BACKGROUND

## Bias-Aware Confidence Intervals for Empirical Bayes Analysis

VIEW 1 EXCERPT

CITES BACKGROUND

#### References

##### Publications referenced by this paper.

SHOWING 1-10 OF 33 REFERENCES

## Population recovery and partial identification

VIEW 3 EXCERPTS

## A Polynomial Time Algorithm for Lossy Population Recovery

VIEW 7 EXCERPTS

HIGHLY INFLUENTIAL

## Finding Heavy Hitters from Lossy or Noisy Data

VIEW 6 EXCERPTS

HIGHLY INFLUENTIAL

## On the learnability of discrete distributions

VIEW 3 EXCERPTS

## Optimal mean-based algorithms for trace reconstruction

VIEW 10 EXCERPTS

HIGHLY INFLUENTIAL

## Sharp bounds for population recovery

VIEW 2 EXCERPTS