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Electronic Colloquium on Computational Complexity

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TR17-045 | 7th March 2017
Noah Fleming, Denis Pankratov, Toniann Pitassi, Robert Robere

Random CNFs are Hard for Cutting Planes

Revisions: 2

The random k-SAT model is the most important and well-studied distribution over
k-SAT instances. It is closely connected to statistical physics; it is used as a testbench for
satisfiablity algorithms, and lastly average-case hardness over this distribution has also
been linked to hardness of approximation via Feige’s hypothesis. In this ... more >>>


TR17-044 | 21st February 2017
Olaf Beyersdorff, Luke Hinde, Ján Pich

Reasons for Hardness in QBF Proof Systems

Revisions: 1

We aim to understand inherent reasons for lower bounds for QBF proof systems and revisit and compare two previous approaches in this direction.

The first of these relates size lower bounds for strong QBF Frege systems to circuit lower bounds via strategy extraction (Beyersdorff & Pich, LICS'16). Here we ... more >>>


TR17-043 | 3rd March 2017
Alexey Milovanov, Nikolay Vereshchagin

Stochasticity in Algorithmic Statistics for Polynomial Time

A fundamental notion in Algorithmic Statistics is that of a stochastic object, i.e., an object having a simple plausible explanation. Informally, a probability distribution is a plausible explanation for $x$ if it looks likely that $x$ was drawn at random with respect to that distribution. In this paper, we ... more >>>



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