Security, privacy, and fairness · MLD-0944
Privacy budget
Parameters describing the strength and composition of a differential-privacy guarantee.
Original reference page · detailed expansion pending. Original definitions, examples, notes and citations are preserved below. New examples are illustrative, not benchmark results.
Original example
Track cumulative privacy loss across training steps.
Original caveat
Smaller epsilon is usually stronger, but context and delta matter.
Context and aliases
Level: Intermediate. Stages: Data · Training · Evaluation · Deployment · Governance.
Tags: ML · DL · SLM · LLM · Security · Privacy · Safety.
Aliases: Epsilon-delta budget.
Related concepts
Concepts linking here
Original references
- The Algorithmic Foundations of Differential Privacy ↗ · Reference link
- Google Machine Learning Glossary ↗ · Consulted
- OWASP Top 10 for LLM Applications ↗ · Reference link
- Original reference URL ↗