Optimizers: How Variables Learn

Variables are tensors you can update. Optimizers compute updates from gradients:

• SGD: w ← w − η g
• Momentum: adds velocity to smooth updates
• Adam: adaptive learning rates per parameter (mean + variance estimates)

Under the hood, these are additional ops in the graph that read gradients and write new values.