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Electronic Colloquium on Computational Complexity

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TR19-036 | 5th March 2019
Pavel Hrubes

On the complexity of computing a random Boolean function over the reals

Revisions: 1

We say that a first-order formula $A(x_1,\dots,x_n)$ over $\mathbb{R}$ defines a Boolean function $f:\{0,1\}^n\rightarrow\{0,1\}$, if for every $x_1,\dots,x_n\in\{0,1\}$, $A(x_1,\dots,x_n)$ is true iff $f(x_1,\dots,x_n)=1$. We show that:

(i) every $f$ can be defined by a formula of size $O(n)$,
(ii) if $A$ is required to have at most $k\geq 1$ ... more >>>


TR19-035 | 5th March 2019
Alexey Milovanov

PIT for depth-4 circuits and Sylvester-Gallai theorem for polynomials


This text is a development of a preprint of Ankit Gupta.

We present an approach for devising a deterministic polynomial time whitekbox identity testing (PIT) algorithm for depth-$4$ circuits with bounded top fanin.
This approach is similar to Kayal-Saraf approach for depth-$3$ circuits. Kayal and Saraf based their ... more >>>


TR19-034 | 5th March 2019
Pavel Hrubes

On $\epsilon$-sensitive monotone computations

Revisions: 1

We show that strong-enough lower bounds on monotone arithmetic circuits or the non-negative rank of a matrix imply unconditional lower bounds in arithmetic or Boolean circuit complexity. First, we show that if a polynomial $f\in {\mathbb {R}}[x_1,\dots, x_n]$ of degree $d$ has an arithmetic circuit of size $s$ then $(x_1+\dots+x_n+1)^d+\epsilon ... more >>>



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