Faster Rectangular Matrix Multiplication by Combination Loss Analysis
François Le Gall
2024年份
8被引次数
9顶会引用
摘要
Duan, Wu and Zhou (FOCS 2023) recently obtained the improved upper bound on the exponent of square matrix multiplication ω < 2.3719 by introducing a new approach to quantify and compensate the “combination loss” in prior analyses of powers of the Coppersmith-Winograd tensor. In this paper we show how to use this new approach to improve the exponent of rectangular matrix multiplication as well. Our main technical contribution is showing how to combine this analysis of the combination loss and the analysis of the fourth power of the Coppersmith-Winograd tensor in the context of rectangular matrix multiplication developed by Le Gall and Urrutia (SODA 2018).
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper9
- New Bounds for Matrix Multiplication: from Alpha to OmegaVirginia Vassilevska Williams, Yinzhan Xu, Zixuan Xu, Renfei ZhouSODA 2024 · 被引用 90 次
- More Asymmetry Yields Faster Matrix MultiplicationJosh Alman, Ran Duan, Virginia Vassilevska Williams, Yinzhan Xu 等SODA 2025 · 被引用 35 次
- Improving the Leading Constant of Matrix MultiplicationJosh Alman, Hantao YuSODA 2025 · 被引用 2 次
- Convex Minimization with Integer Minima in Õ(n4) TimeHaotian Jiang, Yin Tat Lee, Zhao Song, Lichen ZhangSODA 2024 · 被引用 2 次
- Log-concave Sampling from a Convex Body with a Barrier: a Robust and Unified Dikin WalkYuzhou Gu, Nikki Lijing Kuang, Yian Ma, Zhao Song 等NeurIPS 2024 · 被引用 2 次
它引用的顶会 Paper2
相关 Paper
- The Time Complexity of Fully Sparse Matrix MultiplicationAmir Abboud, Karl Bringmann, Nick Fischer, Marvin KünnemannSODA 2024 · 被引用 6 次
- Faster Algorithms for Bounded-Difference Min-Plus ProductShucheng Chi, Ran Duan, Tianle XieSODA 2022 · 被引用 5 次
- Overcomplete Tensor Decomposition via Koszul-Young FlatteningsPravesh K. Kothari, Ankur Moitra, Alexander S. WeinFOCS 2025 · 被引用 1 次
- Fast Batch Matrix Multiplication in CiphertextsJung Hee Cheon, Minsik Kang, Junho LeeCRYPTO 2026 · 被引用 2 次
- Kronecker products, low-depth circuits, and matrix rigidityJosh AlmanSTOC 2021 · 被引用 8 次
