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[2602.15568] Scenario Approach with Post-Design Certification of User-Specified Properties
Summary
This paper introduces a scenario approach for post-design certification of user-specified properties, enhancing reliability without additional test datasets.
Why It Matters
The scenario approach provides a novel framework for ensuring the reliability of machine learning designs by certifying properties after design completion. This is crucial for applications where safety and performance are paramount, particularly in fields like robotics and control systems.
Key Takeaways
- Introduces a two-level framework for design appropriateness.
- Guarantees additional properties useful in post-design evaluation.
- Provides computable upper bounds on risk without extra test data.
- Includes practical examples demonstrating the methodology.
- Enhances understanding of performance indexes from datasets.
Statistics > Methodology arXiv:2602.15568 (stat) [Submitted on 17 Feb 2026] Title:Scenario Approach with Post-Design Certification of User-Specified Properties Authors:Algo Carè, Marco C. Campi, Simone Garatti View a PDF of the paper titled Scenario Approach with Post-Design Certification of User-Specified Properties, by Algo Car\`e and 2 other authors View PDF HTML (experimental) Abstract:The scenario approach is an established data-driven design framework that comes equipped with a powerful theory linking design complexity to generalization properties. In this approach, data are simultaneously used both for design and for certifying the design's reliability, without resorting to a separate test dataset. This paper takes a step further by guaranteeing additional properties, useful in post-design usage but not considered during the design phase. To this end, we introduce a two-level framework of appropriateness: baseline appropriateness, which guides the design process, and post-design appropriateness, which serves as a criterion for a posteriori evaluation. We provide distribution-free upper bounds on the risk of failing to meet the post-design appropriateness; these bounds are computable without using any additional test data. Under additional assumptions, lower bounds are also derived. As part of an effort to demonstrate the usefulness of the proposed methodology, the paper presents two practical examples in H2 and pole-placement problems. Moreover, a method is provided...
