Manifold for Machine Learning Assurance

The increasing use of machine-learning (ML) enabled systems in critical tasks fuels the quest for novel verification and validation techniques yet grounded in accepted system assurance principles. In traditional system development, model-based techniques have been widely adopted, where the central p...

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Bibliographische Detailangaben

Veröffentlicht in:	Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: New Ideas and Emerging Results S. 97 - 100
Hauptverfasser:	Byun, Taejoon, Rayadurgam, Sanjai
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	ACM 01.10.2020
Schlagworte:	Machine learning machine learning testing Manifolds Monitoring neural networks Software testing Task analysis Test pattern generators Training data variational autoencoder
Online-Zugang:	Volltext
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