What is curvature conditioning in Gradient Descent?

Updated May 16, 2026

Short answer

Curvature conditioning measures how well-scaled the optimization problem is.

Deep explanation

A well-conditioned problem has similar curvature in all directions, enabling fast convergence. Poor conditioning causes zig-zagging in Gradient Descent. Conditioning is measured using Hessian eigenvalue ratios.

Real-world example

Training deep networks with poorly scaled features.

Common mistakes

  • Ignoring feature scaling before training.

Follow-up questions

  • What is condition number?
  • How to improve conditioning?

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