### Tensor-Rank and Lower Bounds for Arithmetic FormulasTensor-Rank and Lower Bounds for Arithmetic Formulas Access Restriction
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 Author Raz, Ran Source ACM Digital Library Content type Text Publisher Association for Computing Machinery (ACM) File Format PDF Copyright Year ©2013 Language English
 Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science Subject Keyword Arithmetic circuits ♦ Homogenous circuits ♦ Lower bounds ♦ Multilinear circuits ♦ Tensor rank Abstract We show that any explicit example for a tensor $\textit{A}$ : $[n]^{r}$ → $\textit{F}$ with tensor-rank ≥ $n^{rċ(1™o(1))},$ where $\textit{r}$ = $\textit{r}(\textit{n})$ ≤ log $\textit{n}/log$ log $\textit{n}$ is super-constant, implies an explicit super-polynomial lower bound for the size of general arithmetic formulas over F. This shows that strong enough lower bounds for the size of arithmetic formulas of depth 3 imply super-polynomial lower bounds for the size of general arithmetic formulas. One component of our proof is a new approach for homogenization and multilinearization of arithmetic formulas, that gives the following results: We show that for any $\textit{n}-variate$ homogeneous polynomial $\textit{f}$ of degree $\textit{r},$ if there exists a (fanin-2) formula of size $\textit{s}$ and depth $\textit{d}$ for $\textit{f}$ then there exists a homogeneous formula of size $\textit{O}((\textit{d}+\textit{r}+1$ r) ċ $\textit{s})$ for $\textit{f}.$ In particular, for any $\textit{r}$ ≤ $\textit{O}(log$ $\textit{n}),$ if there exists a polynomial size formula for $\textit{f}$ then there exists a polynomial size homogeneous formula for $\textit{f}.$ This refutes a conjecture of Nisan and Wigderson  and shows that super-polynomial lower bounds for homogeneous formulas for polynomials of small degree imply super-polynomial lower bounds for general formulas. We show that for any $\textit{n}-variate$ set-multilinear polynomial $\textit{f}$ of degree $\textit{r},$ if there exists a (fanin-2) formula of size $\textit{s}$ and depth $\textit{d}$ for $\textit{f},$ then there exists a set-multilinear formula of size $\textit{O}((\textit{d}$ + $2)^{r}$ ċ $\textit{s})$ for $\textit{f}.$ In particular, for any $\textit{r}$ ≤ $\textit{O}(log$ $\textit{n}/log$ log $\textit{n}),$ if there exists a polynomial size formula for $\textit{f}$ then there exists a polynomial size set-multilinear formula for $\textit{f}.$ This shows that super-polynomial lower bounds for set-multilinear formulas for polynomials of small degree imply super-polynomial lower bounds for general formulas. ISSN 00045411 Age Range 18 to 22 years ♦ above 22 year Educational Use Research Education Level UG and PG Learning Resource Type Article Publisher Date 2013-11-01 Publisher Place New York e-ISSN 1557735X Journal Journal of the ACM (JACM) Volume Number 60 Issue Number 6 Page Count 15 Starting Page 1 Ending Page 15

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Source: ACM Digital Library