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Electronic Colloquium on Computational Complexity

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TR19-059 | 18th April 2019
Rohit Agrawal

Samplers and extractors for unbounded functions

Revisions: 1

Blasiok (SODA'18) recently introduced the notion of a subgaussian sampler, defined as an averaging sampler for approximating the mean of functions $f:\{0,1\}^m \to \mathbb{R}$ such that $f(U_m)$ has subgaussian tails, and asked for explicit constructions. In this work, we give the first explicit constructions of subgaussian samplers (and in fact ... more >>>


TR19-058 | 16th April 2019
Pavel Pudlak, Vojtech Rodl

Extractors for small zero-fixing sources

A random variable $X$ is an $(n,k)$-zero-fixing source if for some subset $V\subseteq[n]$, $X$ is the uniform distribution on the strings $\{0,1\}^n$ that are zero on every coordinate outside of $V$. An $\epsilon$-extractor for $(n,k)$-zero-fixing sources is a mapping $F:\{0,1\}^n\to\{0,1\}^m$, for some $m$, such that $F(X)$ is $\epsilon$-close in statistical ... more >>>


TR19-057 | 6th April 2019
Olaf Beyersdorff, Joshua Blinkhorn

Proof Complexity of Symmetry Learning in QBF

For quantified Boolean formulas (QBF), a resolution system with a symmetry rule was recently introduced by Kauers and Seidl (Inf. Process. Lett. 2018). In this system, many formulas hard for QBF resolution admit short proofs.

Kauers and Seidl apply the symmetry rule on symmetries of the original formula. Here we ... more >>>



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