Quantitative Verification-Aided Machine Learning: A Tandem Approach for Architecting Self-Adaptive IoT Systems

Quantitative Verification-Aided Machine Learning: A Tandem Approach for Architecting Self-Adaptive IoT Systems

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  • December 10, 2024
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by Javier Cámara, Henry Muccini and Karthik Vaidhyanathan
Reference:
Quantitative Verification-Aided Machine Learning: A Tandem Approach for Architecting Self-Adaptive IoT Systems (Javier Cámara, Henry Muccini and Karthik Vaidhyanathan), In 2020 IEEE International Conference on Software Architecture, ICSA 2020, Salvador, Brazil, March 16-20, 2020, IEEE, 2020.
Bibtex Entry:
@inproceedings{DBLP:conf/icsa/CamaraMV20,
  author       = {Javier C{'{a}}mara and
                  Henry Muccini and
                  Karthik Vaidhyanathan},
  title        = {Quantitative Verification-Aided Machine Learning: {A} Tandem Approach
                  for Architecting Self-Adaptive IoT Systems},
  booktitle    = {2020 {IEEE} International Conference on Software Architecture, {ICSA}
                  2020, Salvador, Brazil, March 16-20, 2020},
  pages        = {11--22},
  publisher    = {{IEEE}},
  year         = {2020},
  url          = {https://doi.org/10.1109/ICSA47634.2020.00010},
  doi          = {10.1109/ICSA47634.2020.00010},
  timestamp    = {Mon, 05 Feb 2024 00:00:00 +0100},
  biburl       = {https://dblp.org/rec/conf/icsa/CamaraMV20.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

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