algorithm robustness
[/ˈælɡərɪðəm ˈroʊbəstnəs/]
noun
robustez do algoritmo
1. The ability of an algorithm to continue functioning correctly and reliably despite encountering invalid inputs, unexpected conditions, or environmental disturbances
The algorithm robustness was tested by introducing noise into the dataset to ensure it could handle real-world imperfections.
A robustez do algoritmo foi testada introduzindo ruído no conjunto de dados para garantir que pudesse lidar com imperfeições do mundo real.
2. A quality measure of computational algorithms that indicates their capacity to maintain stable performance under various error conditions, edge cases, or constraints
Improving algorithm robustness is critical for machine learning models deployed in production environments.
Melhorar a robustez do algoritmo é crítico para modelos de aprendizado de máquina implantados em ambientes de produção.
3. The degree to which an algorithm remains resistant to failures, maintains accuracy, and adapts to unexpected variations in input data or system parameters
The study focused on algorithm robustness against adversarial attacks in neural networks.
O estudo concentrou-se na robustez do algoritmo contra ataques adversariais em redes neurais.
This is a technical term primarily used in computer science, software engineering, and data science communities in both Brazil and the USA. It has become increasingly important in discussions about artificial intelligence safety and production-grade software systems. The term reflects growing concerns about algorithm reliability in critical applications such as healthcare, finance, and autonomous systems.
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