Leftover Hash Lemma by Mahesh S R ποΈ
Explore the Leftover Hash Lemma and how it extracts near-uniform randomness from weak sources, presented by Mahesh S R.

SIGTACS IITK
442 views β’ Nov 8, 2019

About this video
Topic: Leftover Hash Lemma
Speaker: Mahesh S R
Abstract: A randomness extractor is a function that outputs almost uniform bits from a weakly random entropy source. The Leftover Hash Lemma (LHL) states that universal hash functions are good randomness extractors. LHL leads to simple and efficient extractors and hence has applications in many areas of cryptography and complexity theory.
In this talk, the speaker will give a short description of extractors, discuss the proof for LHL and give a simple application of LHL.
Introduction Audio Credits
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Journey by Jay Hifive & Broken Elegance https://soundcloud.com/brokenelegance
Creative Commons β Attribution 3.0 Unportedβ CC BY 3.0
Free Download / Stream: https://bit.ly/journey-broken-elegance
Music promoted by Audio Library https://youtu.be/eTtyZDU6WZQ
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Speaker: Mahesh S R
Abstract: A randomness extractor is a function that outputs almost uniform bits from a weakly random entropy source. The Leftover Hash Lemma (LHL) states that universal hash functions are good randomness extractors. LHL leads to simple and efficient extractors and hence has applications in many areas of cryptography and complexity theory.
In this talk, the speaker will give a short description of extractors, discuss the proof for LHL and give a simple application of LHL.
Introduction Audio Credits
ββββββββββββββββββββββββββββββ
Journey by Jay Hifive & Broken Elegance https://soundcloud.com/brokenelegance
Creative Commons β Attribution 3.0 Unportedβ CC BY 3.0
Free Download / Stream: https://bit.ly/journey-broken-elegance
Music promoted by Audio Library https://youtu.be/eTtyZDU6WZQ
ββββββββββββββββββββββββββββββ
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Video Information
Views
442
Likes
6
Duration
48:36
Published
Nov 8, 2019