M. Abdullah, M. Töpfer, T. Bureš, P. Hnětynka, M. Kruliš, F. Plášil:
Introducing Estimators—Abstraction for Easy ML Employment in Self-adaptive Architectures, in Proceedings of ECSA 2022 Tracks and Workshops, pp. 370-385, 2023
DOI: 10.1007/978-3-031-36889-9_25
M. Töpfer, M. Abdullah, T. Bureš, P. Hnětynka, M. Kruliš:
Machine-learning abstractions for component-based self-optimizing systems, in International Journal on Software Tools for Technology Transfer 25, pp. 717–731, 2023
DOI: 10.1007/s10009-023-00726-x
P. Hnětynka, M. Kruliš, M. Töpfer, T. Bureš:
Modeling Machine Learning Concerns in Collective Adaptive Systems:, in Proceedings of the 11th International Conference on Model-Based Software and Systems Engineering, Lisbon, Portugal, pp. 55-62, 2023
ISBN: 978-989-758-633-0, DOI: 10.5220/0011693300003402
M. Töpfer, F. Plášil, T. Bureš, P. Hnětynka, M. Kruliš, D. Weyns:
Online ML Self-adaptation in Face of Traps, accepted for publication in Proceedings of ACSOS 2023,Toronto, Canada
M. Töpfer, M. Abdullah, T. Bureš, P. Hnětynka, M. Kruliš:
Ensemble-Based Modeling Abstractions for Modern Self-optimizing Systems, in Proceedings of ISOLA 2022, Rhodes, Greece, pp. 318-334, 2022
DOI: 10.1007/978-3-031-19759-8_20
M. Töpfer, M. Abdullah, M. Kruliš, T. Bureš, P. Hnětynka:
ML-DEECo: a Machine-Learning-Enabled Framework for Self-organizing Components, in Proceedings of ACSOS 2022, Virtual event, 2022
DOI: 10.1109/ACSOSC56246.2022.00033
L. Bulej, T. Bureš, P. Hnětynka, V. Čamra, P. Siegl, M. Töpfer:
IVIS: Highly customizable framework for visualization and processing of IoT data, in Proceedings of EUROMICRO SEAA 2020, Portorož, Slovenia, 2020
DOI: 10.1109/SEAA51224.2020.00095