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Electronic Colloquium on Computational Complexity

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REPORTS > KEYWORD > PROOF:
Reports tagged with proof:
TR07-130 | 3rd December 2007
Ronen Shaltiel, Emanuele Viola

Hardness amplification proofs require majority

Hardness amplification is the fundamental task of
converting a $\delta$-hard function $f : {0,1}^n ->
{0,1}$ into a $(1/2-\eps)$-hard function $Amp(f)$,
where $f$ is $\gamma$-hard if small circuits fail to
compute $f$ on at least a $\gamma$ fraction of the
inputs. Typically, $\eps,\delta$ are small (and
$\delta=2^{-k}$ captures the case ... more >>>


TR09-035 | 26th March 2009
Nicola Galesi, Massimo Lauria

On the Automatizability of Polynomial Calculus

We prove that Polynomial Calculus and Polynomial Calculus with Resolution are not automatizable, unless W[P]-hard problems are fixed parameter tractable by one-side error randomized algorithms. This extends to Polynomial Calculus the analogous result obtained for Resolution by Alekhnovich and Razborov (SIAM J. Computing, 38(4), 2008).

more >>>

TR17-106 | 16th June 2017
Mateus de Oliveira Oliveira, Pavel Pudlak

Representations of Monotone Boolean Functions by Linear Programs

We introduce the notion of monotone linear programming circuits (MLP circuits), a model of
computation for partial Boolean functions. Using this model, we prove the following results:

1. MLP circuits are superpolynomially stronger than monotone Boolean circuits.
2. MLP circuits are exponentially stronger than monotone span programs.
3. ... more >>>


TR19-135 | 2nd October 2019
Michel Goemans, Shafi Goldwasser, Dhiraj Holden

Doubly-Efficient Pseudo-Deterministic Proofs

In [20] Goldwasser, Grossman and Holden introduced pseudo-deterministic interactive proofs for search problems where a powerful prover can convince a probabilistic polynomial time verifier that a solution to a search problem is canonical. They studied search problems for which polynomial time algorithms are not known and for which many solutions ... more >>>




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