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A Blogscursion into the World of Expanders

Comment-link {margin-left:.6em;}. A Blogscursion into the World of Expanders. Friday, December 16, 2005. Recap: A Randomness-Efficient Sampler for Matrix-valued Functions and Applications. Recap: A Randomness-Efficient Sampler for Matrix-valued Functions and Applications. We are given an expander graph G. We are interested in functions f:V- [-1, 1] and aim to calculate the. Expectation E[f]. For this analysis we are given that E[f] = 0, but we can also consider estimating E[g] for functions g where.

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A Blogscursion into the World of Expanders | expanders.blogspot.com Reviews
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Comment-link {margin-left:.6em;}. A Blogscursion into the World of Expanders. Friday, December 16, 2005. Recap: A Randomness-Efficient Sampler for Matrix-valued Functions and Applications. Recap: A Randomness-Efficient Sampler for Matrix-valued Functions and Applications. We are given an expander graph G. We are interested in functions f:V- [-1, 1] and aim to calculate the. Expectation E[f]. For this analysis we are given that E[f] = 0, but we can also consider estimating E[g] for functions g where.
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6 david's lectures
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8 are bitvectors optimal
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A Blogscursion into the World of Expanders | expanders.blogspot.com Reviews

https://expanders.blogspot.com

Comment-link {margin-left:.6em;}. A Blogscursion into the World of Expanders. Friday, December 16, 2005. Recap: A Randomness-Efficient Sampler for Matrix-valued Functions and Applications. Recap: A Randomness-Efficient Sampler for Matrix-valued Functions and Applications. We are given an expander graph G. We are interested in functions f:V- [-1, 1] and aim to calculate the. Expectation E[f]. For this analysis we are given that E[f] = 0, but we can also consider estimating E[g] for functions g where.

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A Blogscursion into the World of Expanders: September 2005

http://expanders.blogspot.com/2005_09_01_archive.html

Comment-link {margin-left:.6em;}. A Blogscursion into the World of Expanders. Tuesday, September 27, 2005. Coming up are applications of expanders. Some of you have already signed up for some topics. (The sign-up process has been a little ad hoc. The dates below are a little flexible, especially for the last few presentations; if anyone who hasn't signed up for a presentation wants to take one of the following dates - or topics - let me know ASAP.). Posted by Manoj Prabhakaran at 2:38 PM. Posted by David...

2

A Blogscursion into the World of Expanders: Recap: The PCP Theorem by Gap Amplification

http://expanders.blogspot.com/2005/12/recap-pcp-theorem-by-gap-amplification.html

Comment-link {margin-left:.6em;}. A Blogscursion into the World of Expanders. Saturday, December 10, 2005. Recap: The PCP Theorem by Gap Amplification. The PCP theorem (almost) states this surprising property that given a proof of answer of some YES/NO problem, there is some scheme that checks just some constant pieces of the proof and decides whether the proof is correct or not, and this decision is with high probability a correct decision. Posted by reza at 7:19 PM. Links to this post:.

3

A Blogscursion into the World of Expanders: Recap: A Randomness-Efficient Sampler for Matrix-valued Functions and Applications

http://expanders.blogspot.com/2005/12/recap-randomness-efficient-sampler-for.html

Comment-link {margin-left:.6em;}. A Blogscursion into the World of Expanders. Friday, December 16, 2005. Recap: A Randomness-Efficient Sampler for Matrix-valued Functions and Applications. Recap: A Randomness-Efficient Sampler for Matrix-valued Functions and Applications. We are given an expander graph G. We are interested in functions f:V- [-1, 1] and aim to calculate the. Expectation E[f]. For this analysis we are given that E[f] = 0, but we can also consider estimating E[g] for functions g where.

4

A Blogscursion into the World of Expanders: David's Lectures

http://expanders.blogspot.com/2005/12/davids-lectures.html

Comment-link {margin-left:.6em;}. A Blogscursion into the World of Expanders. Thursday, December 08, 2005. Sorry, I forgot to post the url of the lecture notes for David's lectures. Meanwhile, I made a few changes. I could not write it up in html so prepared a pdf file:. Http:/ www.geocities.com/hemanta maji/lecture.pdf. Posted by Hemanta K. Maji at 10:26 PM. Links to this post:. Course Blog for "An Excursion into the World of Expanders," offered this Fall at the CS Dept, UIUC. Hemanta K. Maji.

5

A Blogscursion into the World of Expanders: Recap: Are Bitvectors Optimal?

http://expanders.blogspot.com/2005/12/recap-are-bitvectors-optimal.html

Comment-link {margin-left:.6em;}. A Blogscursion into the World of Expanders. Thursday, December 08, 2005. Recap: Are Bitvectors Optimal? In the paper "Are Bitvectors Optimal? Posted by Tracy at 9:44 PM. Links to this post:. Course Blog for "An Excursion into the World of Expanders," offered this Fall at the CS Dept, UIUC. Hemanta K. Maji. The PCP Theorem by Gap Amplification. Undirected ST-connectivity in logspace. Recap: Amplifying one-way functions. Extractors (Phillip Mienk, lecturer).

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Pseudo-random Thoughts: September 2005

http://nitish.blogspot.com/2005_09_01_archive.html

As is probably apparent from the title of this blog, I'm addicted to Computer Science. Fear not, that won't be the sole subject of my musings. I fully expect to write about whatever moves me; politics, books, or what I ate for dinner last night. Part of the adventure for me (and for any readers I might attract) is not knowing what it'll be on any given day. Wednesday, September 14, 2005. I once wished that I could get (academic) credit for blogging. It turns out I now can! Is hilarious as well.

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A Blogscursion into the World of Expanders

Comment-link {margin-left:.6em;}. A Blogscursion into the World of Expanders. Friday, December 16, 2005. Recap: A Randomness-Efficient Sampler for Matrix-valued Functions and Applications. Recap: A Randomness-Efficient Sampler for Matrix-valued Functions and Applications. We are given an expander graph G. We are interested in functions f:V- [-1, 1] and aim to calculate the. Expectation E[f]. For this analysis we are given that E[f] = 0, but we can also consider estimating E[g] for functions g where.

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