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Electronic Colloquium on Computational Complexity

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Reports tagged with matrix product:
TR00-029 | 30th April 2000
Ran Raz, Amir Shpilka

Lower Bounds for Matrix Product, in Bounded Depth Circuits with Arbitrary Gates

Revisions: 1

We prove super-linear lower bounds for the number of edges
in constant depth circuits with $n$ inputs and up to $n$ outputs.
Our lower bounds are proved for all types of constant depth
circuits, e.g., constant depth arithmetic circuits, constant depth
threshold circuits ... more >>>

TR01-060 | 23rd August 2001
Amir Shpilka

Lower bounds for matrix product

We prove lower bounds on the number of product gates in bilinear
and quadratic circuits that
compute the product of two $n \times n$ matrices over finite fields.
In particular we obtain the following results:

1. We show that the number of product gates in any bilinear
(or quadratic) ... more >>>

TR02-012 | 3rd February 2002
Ran Raz

On the Complexity of Matrix Product

We prove a lower bound of $\Omega(m^2 \log m)$ for the size of
any arithmetic circuit for the product of two matrices,
over the real or complex numbers, as long as the circuit doesn't
use products with field elements of absolute value larger than 1
(where $m \times m$ is ... more >>>

TR17-131 | 1st September 2017
Joshua Grochow, Cris Moore

Designing Strassen's algorithm

In 1969, Strassen shocked the world by showing that two n x n matrices could be multiplied in time asymptotically less than $O(n^3)$. While the recursive construction in his algorithm is very clear, the key gain was made by showing that 2 x 2 matrix multiplication could be performed with ... more >>>

TR17-170 | 6th November 2017
Arkadev Chattopadhyay, Michal Koucky, Bruno Loff, Sagnik Mukhopadhyay

Simulation Beats Richness: New Data-Structure Lower Bounds

We develop a technique for proving lower bounds in the setting of asymmetric communication, a model that was introduced in the famous works of Miltersen (STOC'94) and Miltersen, Nisan, Safra and Wigderson (STOC'95). At the core of our technique is a novel simulation theorem: Alice gets a $p \times n$ ... more >>>

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