Optimization formula reference

Gradient Descent Update

Updates parameters in the negative gradient direction.

Open in editor
LaTeX\theta_{t+1}=\theta_t-\eta\nabla J(\theta_t)

Variables

  • Define all variables, domains, and units before substitution.

How to use this formula

Updates parameters in the negative gradient direction.

Important notes

  • Verify assumptions and conventions before use.

Quick example

Apply the gradient descent update to a small known case and verify the result.

Applicability, worked calculation, and verification

Assumptions and domain checks

  • Verify assumptions and conventions before use.
  • Specify the objective, constraints, feasible domain, and any convexity or differentiability assumptions used to justify the result.

Worked example

Input

Output

Apply the gradient descent update to a small known case and verify the result.

Common mistakes

  • Before substituting values into Gradient Descent Update, map each variable to its definition and preserve every sign, exponent, subscript, and grouping mark.
  • Do not treat a stationary point as a global optimum without checking constraints, boundaries, and the required optimality conditions.

Continue the workflow

Use Gradient Descent Update in your own work

  1. Check the domainMatch the variables and assumptions to the problem before substituting values.
  2. Copy the exact notationPreserve grouping, signs, and exponents in \theta_{t+1}=\theta_t-\eta\nabla J(\theta_t).
  3. Edit or convertOpen the expression in the LaTeX editor, then export it for your document or web page.

Review and verification

Last reviewed: 2026-07-23

Automated quality check: Kept noindex until the missing evidence is supplied.

Formula references

Frequently asked questions

What is the Gradient Descent Update used for?

Updates parameters in the negative gradient direction.

Can I copy this formula as LaTeX?

Yes. Copy \theta_{t+1}=\theta_t-\eta\nabla J(\theta_t) or open it in the LaTeX editor.

What should I check before using it?

Confirm that each variable, unit, domain restriction, and assumption matches the problem.

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