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2020 – today
- 2024
[c6]Lorena Poenaru-Olaru
, Natalia Karpova, Luis Cruz, Jan S. Rellermeyer, Arie van Deursen:
Is Your Anomaly Detector Ready for Change? Adapting AIOps Solutions to the Real World. CAIN 2024: 222-233- [i3]Lorena Poenaru-Olaru, Luis Cruz, Jan S. Rellermeyer, Arie van Deursen:
McUDI: Model-Centric Unsupervised Degradation Indicator for Failure Prediction AIOps Solutions. CoRR abs/2401.14093 (2024) - 2023
- [c5]Lorena Poenaru-Olaru, Luis Cruz, Jan S. Rellermeyer, Arie van Deursen:
Maintaining and Monitoring AIOps Models Against Concept Drift. CAIN 2023: 98-99 - [c4]Lorena Poenaru-Olaru, June Sallou, Luis Cruz, Jan S. Rellermeyer, Arie van Deursen:
Retrain AI Systems Responsibly! Use Sustainable Concept Drift Adaptation Techniques. GREENS@ICSE 2023: 17-18 - [i2]Lorena Poenaru-Olaru, Natalia Karpova, Luis Cruz, Jan S. Rellermeyer, Arie van Deursen:
Maintenance Techniques for Anomaly Detection AIOps Solutions. CoRR abs/2311.10421 (2023) - 2022
- [c3]Lorena Poenaru-Olaru, Luis Cruz, Arie van Deursen, Jan S. Rellermeyer:
Are Concept Drift Detectors Reliable Alarming Systems? - A Comparative Study. IEEE Big Data 2022: 3364-3373 - [i1]Lorena Poenaru-Olaru, Luis Cruz, Arie van Deursen, Jan S. Rellermeyer:
Are Concept Drift Detectors Reliable Alarming Systems? - A Comparative Study. CoRR abs/2211.13098 (2022) - 2021
- [c2]Lorena Poenaru-Olaru, Judith Redi, Arthur Hovanesyan, Huijuan Wang:
Default Prediction Using Network Based Features. COMPLEX NETWORKS 2021: 732-743 - [c1]Lorena Poenaru-Olaru:
AutoML: towards automation of machine learning systems maintainability. Middleware Doctoral Symposium 2021: 4-5
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