Simplified derivations for high-dimensional convex learning problems
Simplified derivations for high-dimensional convex learning problems
Statistical physics provides tools for analyzing high-dimensional problems in machine learning and theoretical neuroscience. These calculations, particularly those using the replica method, often involve lengthy derivations that can obscure physical interpretation. We give concise, non-replica derivations of several key results and highlight their underlying similarities. Specifically, we introduce a cavity …