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Pedro Mendes,
Maria Casimiro, Paolo Romano and
David Garlan. HyperJump: Accelerating HyperBand via Risk Modelling. In Proceedings of the 37th AAAI Conference on Artificial Intelligence, 2023.
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| 3 |
Maria Casimiro, Paolo Romano,
David Garlan and Luis Rodrigues. Towards a Framework for Adapting Machine Learning Components. In 2022 IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS), 2022. Presentation Video.
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Maria Casimiro, Paolo Romano,
David Garlan,
Gabriel A. Moreno,
Eunsuk Kang and Mark Klein. Self-Adaptation for Machine Learning Based Systems. In Proceedings of the 1st International Workshop on Software Architecture and Machine Learning (SAML), Springer, Virtual, (Originally Växjö, Sweden), 14 September 2021.
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Maria Casimiro,
David Garlan,
Javier Cámara, Luis Rodrigues and Paolo Romano. A Probabilistic Model Checking Approach to Self-Adapting Machine Learning Systems. In Proceedings of the Third International Workshop on Automated and verifiable Software sYstem DEvelopment (ASYDE), 6 December 2021.
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Maria Casimiro, Diego Didona, Paolo Romano, Luis Rodrigues, Willy Zwaenepoel and
David Garlan. Lynceus: Cost-efficient Tuning and Provisioning of Data Analytic Jobs. In The 40th International Conference on Distributed Computing Systems, Singapore, 8-10 July 2020.
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| 7 |
Pedro Mendes,
Maria Casimiro, Paolo Romano and
David Garlan. TrimTuner: Efficient Optimization of MachineLearning Jobs in the Cloud via Sub-Sampling. In Proceedings of the 2020 Symposium on Modelling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS 2020), 2020.
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