WANG, X. L., & BRORSSON, M. (2024). Augmenting Bankruptcy Prediction Using Reported Behavior of Corporate Restructuring. In Intelligent Computers, Algorithms, and Applications. Springer Nature Singapore. doi:10.1007/978-981-97-0065-3_8 Peer reviewed |
RAC, S., & BRORSSON, M. H. (2024). Cost-aware service placement and scheduling in the Edge-Cloud Continuum. Transactions on Architecture and Code Optimization. doi:10.1145/3640823 Peer reviewed |
RAC, S., & BRORSSON, M. H. (2023). Cost-Effective Scheduling for Kubernetes in the Edge-to-Cloud Continuum. In 2023 IEEE International Conference on Cloud Engineering (IC2E) (pp. 153-160). The Institute of Electrical and Electronics Engineers. doi:10.1109/ic2e59103.2023.00025 Peer reviewed |
KAKATI, S.* , & BRORSSON, M. H.*. (2023). WebAssembly beyond the Web: A Review for the Edge-Cloud Continuum. In 2023 3rd International Conference on Intelligent Technologies, CONIT 2023 (pp. 8). Institute of Electrical and Electronics Engineers Inc. doi:10.1109/CONIT59222.2023.10205816 Peer reviewed * These authors have contributed equally to this work. |
WANG, X. L., Kraussl, Z., ZURAD, M., & BRORSSON, M. H. (2023). Effective Automatic Feature Engineering on Financial Statements for Bankruptcy Prediction. In X. L. WANG, Z. KRÄUSSL, M. Zurad, ... M. H. BRORSSON, Effective Automatic Feature Engineering on Financial Statements for Bankruptcy Prediction. Unknown/unspecified: IEEE Xplore. doi:10.1109/iceccme57830.2023.10252608 Peer reviewed |
Panner Selvam, K., & Brorsson, M. H. (2023). Performance Analysis and Benchmarking of a Temperature Downscaling Deep Learning Model. In 31st Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, Naples, Italy 1-3 March 2023. Peer reviewed |
BLANCO, B., BRORSSON, M. H., & ZURAD, M. (2023). Auto-clustering of Financial Reports Based on Formatting Style and Author’s Fingerprint. In I. Koprinska (Ed.), Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Proceedings. Springer Science and Business Media Deutschland GmbH. doi:10.1007/978-3-031-23633-4_9 Peer reviewed |
Panner Selvam, K., & Brorsson, M. H. (2022). Performance Modeling of Weather Forecast Machine Learning for Efficient HPC. In International Conference on Distributed Computing Systems (ICDCS), Italy 10-13 July 2022 (42nd, pp. 1268-1269). Bologna, Italy: IEEE. doi:10.1109/ICDCS54860.2022.00127 Peer reviewed |
Blanco, B., & Brorsson, M. H. (2022). PROJECT DASHBOARD. Luxembourg, Luxembourg: SnT Uni.lu. |
Wang, X. L., Blanco, B., & Brorsson, M. H. (2022). REPORT OF DATA FUSION AND EVALUATION. Luxembourg, Luxembourg: SNT uni.lu. |
Rac, S., Sanyal, R., & Brorsson, M. H. (2022). A Cloud-Edge Continuum Experimental Methodology applied to a 5G Core Study. Transactions on Computational Science and Computational Intelligence. Peer reviewed |
Rac, S., & Brorsson, M. H. (2021). At the Edge of a Seamless Cloud Experience. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/51871. doi:10.48550/arXiv.2111.06157 |
Blanco, B., & Brorsson, M. H. (2021). DATA DISTRIBUTION API SPECIFICATION. Luxembourg, Luxembourg: SnT Uni.lu. |
Wang, X. L., Blanco, B., & Brorsson, M. H. (2021). REPORT OF DATA SOURCES. Luxembourg, Luxembourg: SnT Uni.lu. |
Du, M., Hammerschmidt, C., Varisteas, G., State, R., Brorsson, M. H., & Zhang, Z. (2019). Time Series Modeling of Market Price in Real-Time Bidding. In 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Peer reviewed |
Du, M., Cowen-Rivers, A. I., Wen, Y., Sakulwongtana, P., Wang, J., Brorsson, M. H., & State, R. (2019). Know Your Enemies and Know Yourself in the Real-Time Bidding Function Optimisation. In Proceedings of the 19th IEEE International Conference on Data Mining Workshops (ICDMW 2019). Peer reviewed |
Oz, I., Bhatti, M. K., Popov, K., & Brorsson, M. H. (2019). Regression-based prediction for task-based program performance. Journal of Circuits, Systems and Computers, 28 (04), 1950060. doi:10.1142/S0218126619500609 Peer reviewed |