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Electronic Colloquium on Computational Complexity

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TR16-045 | 22nd March 2016
Michael Forbes, Mrinal Kumar, Ramprasad Saptharishi

Functional lower bounds for arithmetic circuits and connections to boolean circuit complexity

We say that a circuit $C$ over a field $F$ functionally computes an $n$-variate polynomial $P \in F[x_1, x_2, \ldots, x_n]$ if for every $x \in \{0,1\}^n$ we have that $C(x) = P(x)$. This is in contrast to {syntactically} computing $P$, when $C \equiv P$ as formal polynomials. In this ... more >>>


TR16-044 | 21st March 2016
Kaave Hosseini, Shachar Lovett

Structure of protocols for XOR functions

Revisions: 1

Let $f:\{0,1\}^n \to \{0,1\}$ be a boolean function. Its associated XOR function is the two-party function $f_\oplus(x,y) = f(x \oplus y)$.
We show that, up to polynomial factors, the deterministic communication complexity of $f_{\oplus}$ is equal to the parity decision tree complexity of $f$.
This relies on a novel technique ... more >>>


TR16-043 | 23rd February 2016
Mikolas Janota

On Q-Resolution and CDCL QBF Solving

Q-resolution and its variations provide the underlying proof
systems for the DPLL-based QBF solvers. While (long-distance) Q-resolution
models a conflict driven clause learning (CDCL) QBF solver, it is not
known whether the inverse is also true. This paper provides a negative
answer to this question. This contrasts with SAT solving, ... more >>>



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