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We show that any $n$-variate polynomial computable by a syntactically multilinear circuit of size $\operatorname{poly}(n)$ can be computed by a depth-$4$ syntactically multilinear ($\Sigma\Pi\Sigma\Pi$) circuit of size at most…

Computational Complexity · Computer Science 2019-02-20 Mrinal Kumar , Rafael Oliveira , Ramprasad Saptharishi

In this paper, we study the algebraic formula complexity of multiplying $d$ many $2\times 2$ matrices, denoted $\mathrm{IMM}_{d}$, and show that the well-known divide-and-conquer algorithm cannot be significantly improved at any depth, as…

Computational Complexity · Computer Science 2017-10-17 Suryajith Chillara , Nutan Limaye , Srikanth Srinivasan

Tavenas has recently proved that any n^{O(1)}-variate and degree n polynomial in VP can be computed by a depth-4 circuit of size 2^{O(\sqrt{n}\log n)}. So to prove VP not equal to VNP, it is sufficient to show that an explicit polynomial in…

Computational Complexity · Computer Science 2013-11-18 Suryajith Chillara , Partha Mukhopadhyay

Koiran showed that if a $n$-variate polynomial of degree $d$ (with $d=n^{O(1)}$) is computed by a circuit of size $s$, then it is also computed by a homogeneous circuit of depth four and of size $2^{O(\sqrt{d}\log(d)\log(s))}$. Using this…

Computational Complexity · Computer Science 2014-05-19 Sébastien Tavenas

Agrawal and Vinay [AV08] showed how any polynomial size arithmetic circuit can be thought of as a depth four arithmetic circuit of subexponential size. The resulting circuit size in this simulation was more carefully analyzed by Korian…

Computational Complexity · Computer Science 2017-08-02 Suryajith Chillara , Mrinal Kumar , Ramprasad Saptharishi , V Vinay

We prove exponential lower bounds on the size of homogeneous depth 4 arithmetic circuits computing an explicit polynomial in $VP$. Our results hold for the {\it Iterated Matrix Multiplication} polynomial - in particular we show that any…

Computational Complexity · Computer Science 2014-04-09 Mrinal Kumar , Shubhangi Saraf

Recently, Forbes, Kumar and Saptharishi [CCC, 2016] proved that there exists an explicit $d^{O(1)}$-variate and degree $d$ polynomial $P_{d}\in VNP$ such that if any depth four circuit $C$ of bounded formal degree $d$ which computes a…

Computational Complexity · Computer Science 2021-07-22 Suryajith Chillara

We introduce the polynomial coefficient matrix and identify maximum rank of this matrix under variable substitution as a complexity measure for multivariate polynomials. We use our techniques to prove super-polynomial lower bounds against…

Computational Complexity · Computer Science 2013-02-15 Mrinal Kumar , Gaurav Maheshwari , Jayalal Sarma M. N

Recently, Gupta et.al. [GKKS2013] proved that over Q any $n^{O(1)}$-variate and $n$-degree polynomial in VP can also be computed by a depth three $\Sigma\Pi\Sigma$ circuit of size $2^{O(\sqrt{n}\log^{3/2}n)}$. Over fixed-size finite fields,…

Computational Complexity · Computer Science 2014-01-03 Suryajith Chillara , Partha Mukhopadhyay

We give several new lower bounds on size of homogeneous non-commutative circuits. We present an explicit homogeneous bivariate polynomial of degree $d$ which requires homogeneous non-commutative circuit of size $\Omega(d/\log d)$. For an…

Computational Complexity · Computer Science 2023-01-05 Prerona Chatterjee , Pavel Hrubeš

We prove strengthened lower bounds for constant-depth set-multilinear formulas. More precisely, we show that over any field, there is an explicit polynomial $f$ in VNP defined over $n^2$ variables, and of degree $n$, such that any…

Computational Complexity · Computer Science 2022-05-03 Deepanshu Kush , Shubhangi Saraf

In their paper on the "chasm at depth four", Agrawal and Vinay have shown that polynomials in m variables of degree O(m) which admit arithmetic circuits of size 2^o(m) also admit arithmetic circuits of depth four and size 2^o(m). This…

Computational Complexity · Computer Science 2012-03-26 Pascal Koiran

Let $\mathscr{F}_{n,d}$ be the class of all functions $f:\{-1,1\}^n\to[-1,1]$ on the $n$-dimensional discrete hypercube of degree at most $d$. In the first part of this paper, we prove that any (deterministic or randomized) algorithm which…

Machine Learning · Computer Science 2024-10-23 Alexandros Eskenazis , Paata Ivanisvili , Lauritz Streck

In this paper, we investigate computational power of threshold circuits and other theoretical models of neural networks in terms of the following four complexity measures: size (the number of gates), depth, weight and energy. Here the…

Computational Complexity · Computer Science 2023-06-29 Kei Uchizawa , Haruki Abe

We prove a lower bound of $\Omega(n^2/\log^2 n)$ on the size of any syntactically multilinear arithmetic circuit computing some explicit multilinear polynomial $f(x_1, \ldots, x_n)$. Our approach expands and improves upon a result of Raz,…

Computational Complexity · Computer Science 2017-11-03 Noga Alon , Mrinal Kumar , Ben Lee Volk

Let $A(n, d)$ denote the maximum size of a binary code of length $n$ and minimum Hamming distance $d$. Studying $A(n, d)$, including efforts to determine it as well to derive bounds on $A(n, d)$ for large $n$'s, is one of the most…

Information Theory · Computer Science 2023-05-25 James Chin-Jen Pang , Hessam Mahdavifar , S. Sandeep Pradhan

Multiplication is one of the most fundamental computational problems, yet its true complexity remains elusive. The best known upper bound, by F\"{u}rer, shows that two $n$-bit numbers can be multiplied via a boolean circuit of size $O(n \lg…

Data Structures and Algorithms · Computer Science 2019-03-01 Peyman Afshani , Casper Benjamin Freksen , Lior Kamma , Kasper Green Larsen

We prove a lower bound of $\Omega\left(n^{1.5}\right)$ for the number of product gates in non-commutative arithmetic circuits for an explicit $n$-variate degree-$n$ polynomial $f_{n}$ (over every field). We observe that this implies that…

Computational Complexity · Computer Science 2026-04-27 Ran Raz

We study the size blow-up that is necessary to convert an algebraic circuit of product-depth $\Delta+1$ to one of product-depth $\Delta$ in the multilinear setting. We show that for every positive $\Delta = \Delta(n) = o(\log n/\log \log…

Computational Complexity · Computer Science 2018-04-10 Suryajith Chillara , Christian Engels , Nutan Limaye , Srikanth Srinivasan

We give the first super-polynomial separation in the power of bounded-depth boolean formulas vs. circuits. Specifically, we consider the problem Distance $k(n)$ Connectivity, which asks whether two specified nodes in a graph of size $n$ are…

Computational Complexity · Computer Science 2013-12-03 Benjamin Rossman
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