4 papers
Machines Learn Number Fields, But How? The Case of Galois Groups
Kyu-Hwan Lee, Seewoo Lee
By applying interpretable machine learning methods such as decision trees, we study how simple models can classify the Galois groups of Galois extensions over of degre…
Interpretable Machine Learning for Kronecker Coefficients
Giorgi Butbaia, Kyu-Hwan Lee, Fabian Ruehle
We analyze the saliency of neural networks and employ interpretable machine learning models to predict whether the Kronecker coefficients of the symmetric group are zero or not. Ou…
Mathematical Data Science
Michael R. Douglas, Kyu-Hwan Lee
Can machine learning help discover new mathematical structures? In this article we discuss an approach to doing this which one can call "mathematical data science". In this paradig…
Data-scientific study of Kronecker coefficients
Kyu-Hwan Lee
We take a data-scientific approach to study whether Kronecker coefficients are zero or not. Motivated by principal component analysis and kernel methods, we define loadings of part…