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Electronic Colloquium on Computational Complexity

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TR12-127 | 3rd October 2012
Eshan Chattopadhyay, Adam Klivans, Pravesh Kothari

An Explicit VC-Theorem for Low-Degree Polynomials

Let $X \subseteq \mathbb{R}^{n}$ and let ${\mathcal C}$ be a class of functions mapping $\mathbb{R}^{n} \rightarrow \{-1,1\}.$ The famous VC-Theorem states that a random subset $S$ of $X$ of size $O(\frac{d}{\epsilon^{2}} \log \frac{d}{\epsilon})$, where $d$ is the VC-Dimension of ${\mathcal C}$, is (with constant probability) an $\epsilon$-approximation for ${\mathcal C}$ ... more >>>


TR12-126 | 23rd September 2012
Shiva Kintali, Sinziana Munteanu

Computing Bounded Path Decompositions in Logspace

We present a logspace algorithm to compute path decompositions of bounded pathwidth graphs, thus settling its complexity. Prior to our work, the best known upper bound to compute such decompositions was linear time. We also show that deciding if the pathwidth of a graph is at most a given constant ... more >>>


TR12-125 | 2nd October 2012
Zahra Jafargholi, Hamidreza Jahanjou, Eric Miles, Jaideep Ramachandran, Emanuele Viola

From RAM to SAT

Revisions: 1

Common presentations of the NP-completeness of SAT suffer
from two drawbacks which hinder the scope of this
flagship result. First, they do not apply to machines
equipped with random-access memory, also known as
direct-access memory, even though this feature is
critical in basic algorithms. Second, they incur a
quadratic blow-up ... more >>>



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