The spark randomizer: a probabilistic and supervised learning approach for computing Gröbner bases
Speaker:
Sonja Petrović, Illinois Institute of Technology
Date and Time:
Thursday, June 6, 2024 - 11:30am to 12:30pm
Location:
Fields Institute, Room 230
Abstract:
We place the problem of computing a Gr\"obner basis of a polynomial ideal within the violator space framework in order to use Clarkson's fast sampling algorithm from geometric optimization. The framework requires three ingredients, some of which we provide theoretically, and the missing ones we provide as outputs of a machine learning algorithm. We demonstrate how this blended randomization-and-learning approach can work for symbolic computation. Joint work with Shahrzad Jamshidi.