# XXt Can Be Faster

arXiv: https://arxiv.org/abs/2505.09814 · HTML: https://mlsanity.com/paper/2505.09814/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 25 references that are in the map.
- First posted on arXiv 14 May 2025.

## Builds on (most cited first, 4 of 4)

- [Shampoo: Preconditioned Stochastic Tensor Optimization](https://mlsanity.com/paper/1802.09568/) (2018)
- [Learning Large Neighborhood Search Policy for Integer Programming](https://mlsanity.com/paper/2111.03466/) (2021)
- [A network that learns Strassen multiplication](https://mlsanity.com/paper/1601.07227/) (2016)
- [Efficiently Parallelizable Strassen-Based Multiplication of a Matrix by its Transpose](https://mlsanity.com/paper/2110.13042/) (2021)

## Abstract (arXiv)

We present RXTX, a new algorithm for computing the product of matrix by its transpose XXt for X∈ ℝn× 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 ∞, but also for small matrices including n = 4. The algorithm was discovered by combining Machine Learning-based search methods with Combinatorial Optimization.