Anna Lackinger

Projektass.in Dipl.-Ing.in / BSc

Role

PreDoc Researcher
Distributed Systems, E194-02

Contact

Publications

Adaptive Active Inference Agents for Heterogeneous and Lifelong Federated Learning / Danilenka, A., Furutanpey, A., Casamayor Pujol, V., Sedlak, B., Lackinger, A., Ganzha, M., Paprzycki, M., & Dustdar, S. (2024). Adaptive Active Inference Agents for Heterogeneous and Lifelong Federated Learning. arXiv. https://doi.org/10.34726/8100
Download: PDF (676 KB)
Projects: AloTwin (2023–2025) / INTEND (2024–2026) / TEADAL (2022–2025)
Inference Load-Aware Orchestration for Hierarchical Federated Learning / Lackinger, A., Frangoudis, P., Cilic, I., Furutanpey, A., Murturi, I., Podnar Zarko, I., & Dustdar, S. (2024). Inference Load-Aware Orchestration for Hierarchical Federated Learning. arXiv. https://doi.org/10.34726/8212
Download: PDF (3.93 MB)
Projects: AloTwin (2023–2025) / INTEND (2024–2026)
Cohabitation of Intelligence and Systems: Towards Self-reference in Digital Anatomies / Morichetta, A., Lackinger, A., & Dustdar, S. (2024). Cohabitation of Intelligence and Systems: Towards Self-reference in Digital Anatomies. In 2024 IEEE International Conference on Service-Oriented System Engineering (SOSE) (pp. 102–110). IEEE. https://doi.org/10.1109/SOSE62363.2024.00018
Project: INTEND (2024–2026)
Time Series Predictions for Cloud Workloads: A Comprehensive Evaluation / Lackinger, A., Morichetta, A., & Dustdar, S. (2024). Time Series Predictions for Cloud Workloads: A Comprehensive Evaluation. In 2024 IEEE International Conference on Service-Oriented System Engineering (SOSE) (pp. 36–45). IEEE. https://doi.org/10.1109/SOSE62363.2024.00011
Projects: AloTwin (2023–2025) / INTEND (2024–2026)
Towards accurate Time series predictions for cloud workloads / Lackinger, A. (2023). Towards accurate Time series predictions for cloud workloads [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2023.115061
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