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Electronic Colloquium on Computational Complexity

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TR13-024 | 7th February 2013
Valentine Kabanets, Antonina Kolokolova

Compression of Boolean Functions

We consider the problem of compression for ``easy'' Boolean functions: given the truth table of an $n$-variate Boolean function $f$ computable by some \emph{unknown small circuit} from a \emph{known class} of circuits, find in deterministic time $\poly(2^n)$ a circuit $C$ (no restriction on the type of $C$) computing $f$ so ... more >>>


TR13-023 | 6th February 2013
Alexander A. Sherstov

Approximating the AND-OR Tree

The approximate degree of a Boolean function $f$ is the least degree of a real polynomial
that approximates $f$ within $1/3$ at every point. We prove that the function $\bigwedge_{i=1}^{n}\bigvee_{j=1}^{n}x_{ij}$,
known as the AND-OR tree, has approximate degree $\Omega(n).$ This lower bound is tight
and closes a ... more >>>


TR13-022 | 5th February 2013
Michael Viderman

Strong LTCs with inverse poly-log rate and constant soundness

Revisions: 1

An error-correcting code $C \subseteq \F^n$ is called $(q,\epsilon)$-strong locally testable code (LTC) if there exists a tester that makes at most $q$ queries to the input word. This tester accepts all codewords with probability 1 and rejects all non-codewords $x\notin C$ with probability at least $\epsilon \cdot \delta(x,C)$, where ... more >>>



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