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 165 tok/s
Gemini 2.5 Pro 47 tok/s Pro
GPT-5 Medium 25 tok/s Pro
GPT-5 High 26 tok/s Pro
GPT-4o 81 tok/s Pro
Kimi K2 189 tok/s Pro
GPT OSS 120B 445 tok/s Pro
Claude Sonnet 4.5 35 tok/s Pro
2000 character limit reached

On Two-Stage Guessing (2104.04586v2)

Published 9 Apr 2021 in cs.IT, math.IT, and math.PR

Abstract: Stationary memoryless sources produce two correlated random sequences $Xn$ and $Yn$. A guesser seeks to recover $Xn$ in two stages, by first guessing $Yn$ and then $Xn$. The contributions of this work are twofold: (1) We characterize the least achievable exponential growth rate (in $n$) of any positive $\rho$-th moment of the total number of guesses when $Yn$ is obtained by applying a deterministic function $f$ component-wise to $Xn$. We prove that, depending on $f$, the least exponential growth rate in the two-stage setup is lower than when guessing $Xn$ directly. We further propose a simple Huffman code-based construction of a function $f$ that is a viable candidate for the minimization of the least exponential growth rate in the two-stage guessing setup. (2) We characterize the least achievable exponential growth rate of the $\rho$-th moment of the total number of guesses required to recover $Xn$ when Stage 1 need not end with a correct guess of $Yn$ and without assumptions on the stationary memoryless sources producing $Xn$ and $Yn$.

Citations (2)

Summary

We haven't generated a summary for 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.