When did Majority become the stablest? (Part 2)

The first question we'd like to answer is this: which is the monotone, balanced, transitive Boolean function which is least sensitive to bit-flips? We know that Majority is the worst possible with $latex NS( Maj) = \Theta(1/\sqrt{n})$. The new champion turns out to be the Tribes function first studied by Ben-Or and Linial. $latex Tribes_{s,w}$ … Continue reading When did Majority become the stablest? (Part 2)

When did Majority become the stablest?

The fireworks happening over at Ryan O'Donnell's blog reminded me of something that always puzzles me: Is Majority the Stablest? Or the Unstablest? Consider the class of all monotone, balanced Boolean functions $latex f:\{-1,1\}^n \rightarrow \{-1,1\}$. We define the noise sensitivity $latex NS(f)$ of a function $latex f$ as $latex NS(f) = P_{x,e}[f(x) \neq f( … Continue reading When did Majority become the stablest?

Aleksander Madry and David Steurer win ACM honorable mention

Every year the ACM gives out an award for the best doctoral dissertation, as well as up to 3 honorable mentions. This year, both honorable mentions were given to CS theorists: Aleksander Madry and David Steurer (the dissertation award was given to Seth Cooper for his work on protein folding games). Both Aleksander's and David's … Continue reading Aleksander Madry and David Steurer win ACM honorable mention

Exact Algorithms from Approximation Algorithms? (part 2)

As promised in the previous post, I will explain how an algorithm designed for the approximate near neighbor problem, the LSH algorithm, leads to a solution for the exact near neighbor problem (henceforth NNS). While, the algorithm for the exact problem will not have full guarantees, we will be able to give some partial guarantees. Usually … Continue reading Exact Algorithms from Approximation Algorithms? (part 2)

Exact Algorithms from Approximation Algorithms? (part 1)

One great "soft" challenge in (T)CS I find to be how to go on to find useful algorithms for problems that we believe (or have even proven!) to be hard in general. Let me explain by giving the all-too-common-example: Practitioner: I need to solve problem X. Theoretician: Nice question, let me think... Hm, it seems hard. … Continue reading Exact Algorithms from Approximation Algorithms? (part 1)