Generative Adversarial Symmetry Discovery
Jianke Yang, Robin Walters, et al.
ICML 2023
In this article we present a systematic approach to the derivation of families of high-performance algorithms for a large set of frequently encountered dense linear algebra operations. As part of the derivation a constructive proof of the correctness of the algorithm is generated. The article is structured so that it can be used as a tutorial for novices. However, the method has been shown to yield new high-performance algorithms for well-studied linear algebra operations and should also be of interest to those who wish to produce best-in-class high-performance codes. © 2005 ACM.
Jianke Yang, Robin Walters, et al.
ICML 2023
Salvatore Certo, Anh Pham, et al.
Quantum Machine Intelligence
T. Graham, A. Afzali, et al.
Microlithography 2000
Richard M. Karp, Raymond E. Miller
Journal of Computer and System Sciences