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Results: 11
Number of items: 11
  • Open Access
    Chen, X., Liu, H., & Mohammadi Ziabari, S. (2025). Efficient Sparse MLPs Through Motif-Level Optimization Under Resource Constraints. AI, 6(10), Article 266. https://doi.org/10.3390/ai6100266
  • Open Access
    Liu, H. (2024). Robust resource management for time-critical tasks in the cloud-edge continuum. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Xin, R., Liu, H., Chen, P., & Zhao, Z. (2023). Robust and accurate performance anomaly detection and prediction for cloud applications: a novel ensemble learning-based framework. Journal of Cloud Computing, 12, Article 7. https://doi.org/10.1186/s13677-022-00383-6
  • Open Access
    Liu, H., Chen, P., Ouyang, X., Gao, H., Yan, B., Grosso, P., & Zhao, Z. (2023). Robustness challenges in Reinforcement Learning based time-critical cloud resource scheduling: A Meta-Learning based solution. Future Generation Computer Systems, 146, 18-33. https://doi.org/10.1016/j.future.2023.03.029
  • Open Access
    Liu, H., Xin, R., Chen, P., Gao, H., Grosso, P., & Zhao, Z. (2023). Robust-PAC time-critical workflow offloading in edge-to-cloud continuum among heterogeneous resources. Journal of Cloud Computing, 12, Article 58. https://doi.org/10.1186/s13677-023-00434-6
  • Open Access
    Liu, H., Oudejans, M., Xin, R., Grosso, P., & Zhao, Z. (2023). A Performance-Adaptive and Time-Monitored Autonomous Ticket Booking Service in Cloud. In 2023 IEEE 32nd International Symposium on Industrial Electronics (ISIE): 19-21 June, 2023, Helsinki-Espoo, Finland : proceedings (pp. 940-945). IEEE. https://doi.org/10.1109/ISIE51358.2023.10228152
  • Chen, P., Liu, H., Xin, R., Carval, T., Zhao, J., Xia, Y., & Zhao, Z. (2022). Effectively Detecting Operational Anomalies In Large-Scale IoT Data Infrastructures By Using A GAN-Based Predictive Model. Computer Journal, 65(11), 2909-2925. https://doi.org/10.1093/comjnl/bxac085
  • Li, M., Su, J., Liu, H., Zhao, Z., Ouyang, X., & Zhou, H. (2022). The Extreme Counts: Modeling the Performance Uncertainty of Cloud Resources with Extreme Value Theory. In J. Troya, B. Medjahed, M. Piattini, L. Yao, P. Fernández, & A. Ruiz-Cortés (Eds.), Service-Oriented Computing: 20th International Conference, ICSOC 2022, Seville, Spain, November 29–December 2, 2022 : proceedings (pp. 498-512). (Lecture Notes in Computer Science; Vol. 13740). Springer. https://doi.org/10.1007/978-3-031-20984-0_35
  • Open Access
    Liu, H., Xin, R., Chen, P., & Zhao, Z. (2022). Multi-Objective Robust Workflow Offloading in Edge-to-Cloud Continuum. In C. A. Ardagna, N. Atukorala, R. Buyya, C. K. Chang, R. N. Chang, E. Damiani, G. B. Dasgupta, F. Gagliardi, C. Hagleitner, D. Milojicic, T. M. H. Trong, R. Ward, F. Xhafa, & J. Zhang (Eds.), 2022 IEEE 15th International Conference on Cloud Computing (IEEE CLOUD 2022): proceedings : hybrid conference, Barcelona, Spain, 11-15 July 2022 (pp. 469-478). IEEE Computer Society. https://doi.org/10.1109/CLOUD55607.2022.00070
  • Open Access
    Xin, R., Stallinga, S., Liu, H., Chen, P., & Zhao, Z. (2022). Provenance-enhanced Root Cause Analysis for Jupyter Notebooks. In 2022 IEEE/ACM 15th International Conference on Utility and Cloud Computing: UCC 2022 : Vancouver, Washington, USA, 6-9 December 2022 : proceedings (pp. 327-333). IEEE. https://doi.org/10.1109/UCC56403.2022.00058, https://doi.org/10.1109/UCC56403.2022.00058
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