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 150 tok/s
Gemini 2.5 Pro 46 tok/s Pro
GPT-5 Medium 26 tok/s Pro
GPT-5 High 28 tok/s Pro
GPT-4o 80 tok/s Pro
Kimi K2 211 tok/s Pro
GPT OSS 120B 435 tok/s Pro
Claude Sonnet 4.5 35 tok/s Pro
2000 character limit reached

Pseudorandomness for concentration bounds and signed majorities (1411.4584v1)

Published 17 Nov 2014 in cs.CC

Abstract: The problem of constructing pseudorandom generators that fool halfspaces has been studied intensively in recent times. For fooling halfspaces over the hypercube with polynomially small error, the best construction known requires seed-length O(log2 n) (MekaZ13). Getting the seed-length down to O(log(n)) is a natural challenge in its own right, which needs to be overcome in order to derandomize RL. In this work we make progress towards this goal by obtaining near-optimal generators for two important special cases: 1) We give a near optimal derandomization of the Chernoff bound for independent, uniformly random bits. Specifically, we show how to generate a x in {1,-1}n using $\tilde{O}(\log (n/\epsilon))$ random bits such that for any unit vector u, <u,x> matches the sub-Gaussian tail behaviour predicted by the Chernoff bound up to error eps. 2) We construct a generator which fools halfspaces with {0,1,-1} coefficients with error eps with a seed-length of $\tilde{O}(\log(n/\epsilon))$. This includes the important special case of majorities. In both cases, the best previous results required seed-length of $O(\log n + \log2(1/\epsilon))$. Technically, our work combines new Fourier-analytic tools with the iterative dimension reduction techniques and the gradually increasing independence paradigm of previous works (KaneMN11, CelisRSW13, GopalanMRTV12).

Citations (5)

Summary

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

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

Open Questions

We haven't generated a list of open questions 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.