The interactive film is in the book's Companion

Play it, pause it, turn it and drag it with Mathematics for AI and Machine Learning.

Get the book

Momentum Methods: Second-Order ODE

Chapter 20 · Mathematics for AI and Machine Learning · Advanced · 1:36

An interactive live film: Nesterov acceleration on the narrow quadratic valley; inertia shoots past the floor while 3/t damping carries the particle rapidly down the flat axis to achieve O(1/t^2) convergence.

Narration

Gradient descent and gradient flow follow the steepest slope. In an elongated valley, they crawl along the floor and waste steps oscillating against steep walls.

Momentum changes the game. Adding inertia turns first-order gradient flow into a second-order differential equation, like a heavy ball rolling in a potential.

The rest of the narration is in the book's Companion.

More from Chapter 20

Interactive1:45Flow Matching: Velocity Fields and the Continuity EquationChapter 20Preview1:28From a Residual Network to a Neural ODEChapter 20Preview1:27Gradient Flow: Gradient Descent With Infinitely Small StepsChapter 20Preview1:26Memory by Orthogonal Projection (HiPPO)Chapter 20Preview1:34Probability Flow ODE: Deterministic Paths, Identical MarginalsChapter 20Preview1:40Backward Error Analysis: What Gradient Descent FollowsChapter 20Preview1:46Rectified Flow: Straightening by RetrainingChapter 20