Abstract
There has been a growing need to devise processes that can create comprehensive datasets in the world of Computer Algebra, both for accurate benchmarking and for new intersections with machine learning technology. We present here a method to generate integrands that are guaranteed to be integrable, dubbed the LIOUVILLE method. It is based on Liouville's theorem and the Parallel Risch Algorithm for symbolic integration. We show that this data generation method retains the best qualities of previous data generation methods, while overcoming some of the issues built into that prior work. The LIOUVILLE generator is able to generate sufficiently complex and realistic integrands, and could be used for benchmarking or machine learning training tasks related to symbolic integration.
| Original language | English |
|---|---|
| Title of host publication | Computer Algebra in Scientific Computing |
| Subtitle of host publication | 26th International Workshop, CASC 2024, Rennes, France, September 2–6, 2024, Proceedings |
| Editors | François Boulier, Chenqi Mou, Timur M. Sadykov, Evgenii V. Vorozhtsov |
| Publisher | Springer |
| Chapter | 4 |
| Pages | 47-62 |
| Number of pages | 16 |
| Volume | 14938 |
| Edition | 1 |
| ISBN (Electronic) | 978-3-031-69070-9 |
| ISBN (Print) | 978-3-031-69069-3 |
| DOIs | |
| Publication status | Published - 21 Aug 2024 |
| Event | 26th International Computer Algebra in Scientific Computing - Rennes, France Duration: 2 Sept 2024 → 6 Sept 2024 https://casc-conference.org/ |
Publication series
| Name | Lecture Notes in Computer Science |
|---|---|
| Publisher | Springer |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Conference
| Conference | 26th International Computer Algebra in Scientific Computing |
|---|---|
| Abbreviated title | CASC 2024 |
| Country/Territory | France |
| City | Rennes |
| Period | 2/09/24 → 6/09/24 |
| Internet address |
Bibliographical note
© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AGThe final publication is available at Springer via http://dx.doi.org/10.1007/978-3-031-69070-9_4
Copyright © and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders.
This document is the author’s post-print version, incorporating any revisions agreed during the peer-review process. Some differences between the published version and this version may remain and you are advised to consult the published version if you wish to cite from it.
Funding
The authors would like to thank James H. Davenport for helpful discussion on the Parallel Risch algorithm. Matthew England is supported by EPSRC Project EP/T015748/1, Pushing Back the Doubly-Exponential Wall of Cylindrical Algebraic Decomposition (the DEWCAD Project). Rashid Barket is supported by a scholarship provided by Maplesoft and Coventry University.
| Funders | Funder number |
|---|---|
| Engineering and Physical Sciences Research Council | EP/T015748/1 |
| Maplesoft | |
| Coventry University |
Keywords
- Computer algebra
- Symbolic computation
- Symbolic integration
- Data generation
- Machine learning
