Optimization
Arg Min and Arg Max Explained
Separate the optimizing input from the minimum or maximum objective value and include domains and constraints.
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Optimization and Mathematical Modeling Guides
Write objectives, constraints, argmin and argmax expressions, convexity conditions, KKT notation, and model error measures with clear domains and assumptions.
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This hub is the primary overview
The narrower references below remain available for specific notation questions, while this page owns the broad subject intent and prevents unrelated guides from being consolidated together.
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These pages answer narrower notation questions and link back to this hub; they are intentionally noindex to reduce cannibalization.
Optimization
Convex Functions and Jensen’s Inequality
Check convexity domains, weights, expectations, and equality cases.
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Convexity and Jensen Notation
Use convex combinations, epigraphs, Hessians, inequalities, and expectation notation without losing assumptions.
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Gradient Descent Notation and Step Sizes
Document iterates, gradients, learning rates, stopping criteria, and constrained updates in optimization algorithms.
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KKT Conditions Guide
Separate stationarity, primal feasibility, dual feasibility, and complementary slackness.
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Lagrange Multiplier Workflow
Set up objectives, equality constraints, multipliers, and second-order checks.
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Linear Programming Standard Form
Translate objectives and constraints into a consistent matrix convention.
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Optimization Constraints and KKT Notation
Read primal feasibility, dual feasibility, stationarity, complementary slackness, and multiplier signs.
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Optimization Duality Notation
Distinguish primal variables, dual variables, bounds, gaps, and strong duality.
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Optimization Models: Common Errors and Verification
Common Errors and Verification for optimization models: write, format, verify, and publish clear definitions, assumptions, examples, accessible markup, and portable notation.
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Optimization Models: LaTeX Formatting Guide
LaTeX Formatting Guide for optimization models: write, format, verify, and publish clear definitions, assumptions, examples, accessible markup, and portable notation.
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Optimization Models: Notation Reference
Notation Reference for optimization models: write, format, verify, and publish clear definitions, assumptions, examples, accessible markup, and portable notation.
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