Scaling laws have been one of the key achievements of theoretical analysis in various fields of applied mathematics and computer science, answering the following key question: How fast does my method or my algorithm converge as a function of (potentially partially) observable problem parameters. For supervised machine learning and statistics, probably the simplest and oldest…