Ben Recht • 2/11/2026

Searching for Stability

This academic blog post, part of a lecture series, examines the deep connections between optimization methods in machine learning (e.g., gradient descent, accelerated methods) and control theory. It explains how convergence proofs for these algorithms use Lyapunov functions, similar to analyzing the stability of dynamical systems, and frames gradient-based optimizers as analogous to PID controllers.

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#Machine Learning #optimization #Gradient Descent