$XX^{t}$ Can Be Faster

Dmitry Rybin, Yushun Zhang, Zhi-Quan Luo
5/14/2025
cs.DScs.AIcs.LG

No official code found. Best implementation: benearnthof/rxtx (2 stars, MIT, last commit 2025-05-18).

Abstract

We present RXTX, a new algorithm for computing the product of matrix by its transpose $XX^{t}$ for $X\in \mathbb{R}^{n\times m}$. RXTX uses $5\%$ fewer multiplications and $5\%$ fewer operations (additions and multiplications) than State-of-the-Art algorithms. Note that the accelerations not only holds asymptotically for large matrices with $n \rightarrow \infty$, but also for small matrices including $n = 4$. The algorithm was discovered by combining Machine Learning-based search methods with Combinatorial Optimization.

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Code Implementations(1)

benearnthof/rxtxCommunity72%
MIT

RXTX: XXᵀ Can Be Faster

21PythonMay 17, 20251 years agoMIT
machine-learningmatrix-multiplicationnumerical-methodsreference-implementation

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Cite this paper

@article{rybin2025xxt,
  title  = {$XX^{t}$ Can Be Faster},
  author = {Dmitry Rybin and Yushun Zhang and Zhi-Quan Luo},
  year   = {2025},
  eprint = {2505.09814},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2505.09814v2}
}

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