Mini-Batching, Gradient-Clipping, First-versus Second-Order: What Works in Gradient-Based Coefficient Optimisation for Symbolic Regression'

The aim of Symbolic Regression (SR) is to discover interpretable expressions that accurately describe data. The accuracy of an expression depends on both its structure and coefficients. To keep the structure simple enough to be interpretable, effective coefficient optimisation becomes key. Gradient-based optimisation is clearly effective at...