Integrating ML and Verification for Self-Adaptive IoT Systems

Listen to this interview of Javier Cámara, Associate Professor, Department of Computer Science, University of Málaga, Spain. We talk about the paper Cámara et al. Quantitative Verification-Aided Machine Learning: A Tandem Approach for Architecting Self-Adaptive IoT Systems.

Javier Cámara : "Yes, it had been an option, at one point during revising, to have the preliminaries up in the paper before the overview of our approach was presented. However, we felt that presenting the preliminaries after we have presented the bird's eye view of our approach was going to provide our reader with a rationale for why each element is described and explained there. We wouldn't have established that sort of rationale if we'd presented those elements earlier, or to establish that, we would have needed to repeat quite a lot in the text."

Link to Cámara et al. Quantitative Verification-Aided Machine Learning: A Tandem Approach for Architecting Self-Adaptive IoT Systems

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