A Machine Learning Based Software Pipeline to Pick the Variable Ordering for Algorithms with Polynomial Inputs

DOI10.1007/978-3-030-52200-1_30zbMath1503.68311arXiv2005.11251OpenAlexW3026474523MaRDI QIDQ5041068

Matthew England, Dorian Florescu

Publication date: 13 October 2022

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2005.11251

zbMATH Keywords

mathematical softwarecylindrical algebraic decompositionmachine learningvariable orderingScikit-Learn

Mathematics Subject Classification ID

Symbolic computation and algebraic computation (68W30) Learning and adaptive systems in artificial intelligence (68T05) Computational real algebraic geometry (14Q30)

Related Items (1)

Explainable AI insights for symbolic computation: a case study on selecting the variable ordering for cylindrical algebraic decomposition

Uses Software

• Scikit
• FORM
• Theoryguru
• DeepMath

Cites Work

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• Quantifier elimination by cylindrical algebraic decomposition based on regular chains

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