Glauner, P., Migliosi, A., Meira, J. A., Valtchev, P., State, R., & Bettinger, F. (2017). Is Big Data Sufficient for a Reliable Detection of Non-Technical Losses? In Proceedings of the 19th International Conference on Intelligent System Applications to Power Systems (ISAP 2017). Peer reviewed |
Blaiech, K., Hamadi, S., Hommes, S., Valtchev, P., Cherkaoui, O., & State, R. (2017). Rule Compilation in Multi-Tenant Networks. In Rule Compilation in Multi-Tenant Networks (pp. 97-98). Beijing, China: IEEE. doi:10.1109/ANCS.2017.34 Peer reviewed |
Glauner, P., Meira, J. A., Valtchev, P., State, R., & Bettinger, F. (2017). The Challenge of Non-Technical Loss Detection using Artificial Intelligence: A Survey. International Journal of Computational Intelligence Systems, 10 (1), 760-775. doi:10.2991/ijcis.2017.10.1.51 Peer reviewed |
Camino, R. D., State, R., Montero, L., & Valtchev, P. (2017). Finding Suspicious Activities in Financial Transactions and Distributed Ledgers. In Proceedings of the 17th IEEE International Conference on Data Mining Workshops (ICDMW 2017). Peer reviewed |
Meira, J. A., Glauner, P., State, R., Valtchev, P., Dolberg, L., Bettinger, F., & Duarte, D. (2017). Distilling Provider-Independent Data for General Detection of Non-Technical Losses. In Power and Energy Conference, Illinois 23-24 February 2017. Peer reviewed |
Glauner, P., Du, M., Paraschiv, V., Boytsov, A., Lopez Andrade, I., Meira, J. A., Valtchev, P., & State, R. (2017). The Top 10 Topics in Machine Learning Revisited: A Quantitative Meta-Study. In Proceedings of the 25th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2017). Peer reviewed |
Hamadi, S., Blaiech, K., Valtchev, P., Cherkaoui, O., & State, R. (2016). Compiling packet forwarding rules for switch pipelined architecture. In IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications. Peer reviewed |