Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 134 tok/s
Gemini 2.5 Pro 41 tok/s Pro
GPT-5 Medium 30 tok/s Pro
GPT-5 High 23 tok/s Pro
GPT-4o 99 tok/s Pro
Kimi K2 190 tok/s Pro
GPT OSS 120B 425 tok/s Pro
Claude Sonnet 4.5 37 tok/s Pro
2000 character limit reached

On Non-Interactive Simulation of Joint Distributions (1505.00769v2)

Published 4 May 2015 in cs.IT and math.IT

Abstract: We consider the following non-interactive simulation problem: Alice and Bob observe sequences $Xn$ and $Yn$ respectively where ${(X_i, Y_i)}_{i=1}n$ are drawn i.i.d. from $P(x,y),$ and they output $U$ and $V$ respectively which is required to have a joint law that is close in total variation to a specified $Q(u,v).$ It is known that the maximal correlation of $U$ and $V$ must necessarily be no bigger than that of $X$ and $Y$ if this is to be possible. Our main contribution is to bring hypercontractivity to bear as a tool on this problem. In particular, we show that if $P(x,y)$ is the doubly symmetric binary source, then hypercontractivity provides stronger impossibility results than maximal correlation. Finally, we extend these tools to provide impossibility results for the $k$-agent version of this problem.

Citations (44)

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.