Machine Learning Parameter Systems, Noether Normalisations and Quasi-stable Positions

Machine Learning Parameter Systems, Noether Normalisations and Quasi-stable Positions

Co-author(s): Amir Hashemi and Mahshid Mirhashemi

Reference: Preprint Isfahan and Kassel Universities 2023

Description: We study how different machine learning models may be used to put ideals into quasi-stable position (a generic position that shares many properties with the much harder to reach generic initial ideal - see [85] ). Based on a batch of 10.000 random ideals, we conclude that machine learning is much more efficient than human heuristics for this problem.

PDF File:

(416 kB)

Home, Last update: Tue Sep 19 10:03:40 2023