A Refined Laser Method and Faster Matrix Multiplication
October 12, 2020 · Declared Dead · 🏛 ACM-SIAM Symposium on Discrete Algorithms
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Josh Alman, Virginia Vassilevska Williams
arXiv ID
2010.05846
Category
cs.DS: Data Structures & Algorithms
Cross-listed
cs.CC,
math.CO
Citations
512
Venue
ACM-SIAM Symposium on Discrete Algorithms
Last Checked
2 months ago
Abstract
The complexity of matrix multiplication is measured in terms of $ω$, the smallest real number such that two $n\times n$ matrices can be multiplied using $O(n^{ω+ε})$ field operations for all $ε>0$; the best bound until now is $ω<2.37287$ [Le Gall'14]. All bounds on $ω$ since 1986 have been obtained using the so-called laser method, a way to lower-bound the `value' of a tensor in designing matrix multiplication algorithms. The main result of this paper is a refinement of the laser method that improves the resulting value bound for most sufficiently large tensors. Thus, even before computing any specific values, it is clear that we achieve an improved bound on $ω$, and we indeed obtain the best bound on $ω$ to date: $$ω< 2.37286.$$ The improvement is of the same magnitude as the improvement that [Le Gall'14] obtained over the previous bound [Vassilevska W.'12]. Our improvement to the laser method is quite general, and we believe it will have further applications in arithmetic complexity.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
📜 Similar Papers
In the same crypt — Data Structures & Algorithms
R.I.P.
👻
Ghosted
R.I.P.
👻
Ghosted
Relief-Based Feature Selection: Introduction and Review
R.I.P.
👻
Ghosted
Route Planning in Transportation Networks
R.I.P.
👻
Ghosted
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration
R.I.P.
👻
Ghosted
Hierarchical Clustering: Objective Functions and Algorithms
R.I.P.
👻
Ghosted
Graph Isomorphism in Quasipolynomial Time
Died the same way — 👻 Ghosted
R.I.P.
👻
Ghosted
Language Models are Few-Shot Learners
R.I.P.
👻
Ghosted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
R.I.P.
👻
Ghosted
XGBoost: A Scalable Tree Boosting System
R.I.P.
👻
Ghosted