Publications

Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning

Okanovic, P., Waleffe, R., Mageirakos, V. , Nikolakakis, K. E., Karbasi, A., Kalogerias, D., ... & Rekatsinas, T. (2023). Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning. arXiv preprint arXiv:2305.18424.

Efficient Massively Parallel Join Optimization for Large Queries

Mancini, R., Karthik, S., Chandra, B., Mageirakos, V., & Ailamaki, A. (2022, June). Efficient massively parallel join optimization for large queries. In Proceedings of the 2022 International Conference on Management of Data (pp. 122-135).

Efficient GPU-accelerated Join Optimization for Complex Queries

Mageirakos, V., Mancini, R., Karthik, S., Chandra, B., & Ailamaki, A. (2022, May). Efficient GPU-accelerated Join Optimization for Complex Queries. In 2022 IEEE 38th International Conference on Data Engineering (ICDE) (pp. 3190-3193). IEEE.

Preparing distributed computing operations for the HL-LHC era with Operational Intelligence

Di Girolamo, A., Legger, F., Paparrigopoulos, P., Schovancová, J., Beermann, T., Boehler, M., Bonacorsi, D., Clissa, L., Decker de Sousa, L., Diotalevi, T., Giommi, L., Grigorieva, M., Giordano, D., Hohn, D., Javůrek, T., Jezequel, S., Kuznetsov, V., Lassnig, M., Mageirakos, V., Olocco, M., … Tuckus, N. (2022). Preparing Distributed Computing Operations for the HL-LHC Era With Operational Intelligence. Frontiers in big data, 4, 753409