# The Power of Shared Randomness in Uncertain Communication

**Authors:** Badih Ghazi, Madhu Sudan

arXiv: 1705.01082 · 2017-05-03

## TL;DR

This paper explores the impact of shared randomness in uncertain communication, demonstrating that public randomness can significantly reduce communication complexity compared to private randomness, and establishing new bounds and separations.

## Contribution

It provides the first separation between private-coin and public-coin uncertain communication complexities and improves lower bounds for public-coin protocols under uncertainty.

## Key findings

- Public randomness reduces communication complexity in uncertain settings.
- Private-coin protocols can require significantly more communication than public-coin protocols.
- New lower bounds demonstrate the power of public randomness in uncertain communication.

## Abstract

In a recent work (Ghazi et al., SODA 2016), the authors with Komargodski and Kothari initiated the study of communication with contextual uncertainty, a setup aiming to understand how efficient communication is possible when the communicating parties imperfectly share a huge context. In this setting, Alice is given a function $f$ and an input string $x$, and Bob is given a function $g$ and an input string $y$. The pair $(x,y)$ comes from a known distribution $\mu$ and $f$ and $g$ are guaranteed to be close under this distribution. Alice and Bob wish to compute $g(x,y)$ with high probability. The previous work showed that any problem with one-way communication complexity $k$ in the standard model has public-coin communication $O(k(1+I))$ bits in the uncertain case, where $I$ is the mutual information between $x$ and $y$. A lower bound of $\Omega(\sqrt{I})$ bits on the public-coin uncertain communication was also shown. An important question that was left open is the power that public randomness brings to uncertain communication. Can Alice and Bob achieve efficient communication amid uncertainty without using public randomness? How powerful are public-coin protocols in overcoming uncertainty? Motivated by these two questions:   - We prove the first separation between private-coin uncertain communication and public-coin uncertain communication. We exhibit a function class for which the communication in the standard model and the public-coin uncertain communication are $O(1)$ while the private-coin uncertain communication is a growing function of the length $n$ of the inputs.   - We improve the lower-bound of the previous work on public-coin uncertain communication. We exhibit a function class and a distribution (with $I \approx n$) for which the one-way certain communication is $k$ bits but the one-way public-coin uncertain communication is at least $\Omega(\sqrt{k} \cdot \sqrt{I})$ bits.

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/1705.01082/full.md

## Figures

8 figures with captions in the complete paper: https://tomesphere.com/paper/1705.01082/full.md

## References

33 references — full list in the complete paper: https://tomesphere.com/paper/1705.01082/full.md

---
Source: https://tomesphere.com/paper/1705.01082