Camino, R. D. (2020). Machine Learning Techniques for Suspicious Transaction Detection and Analysis [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/44939 |
Camino, R. D., Ferreira Torres, C., Baden, M., & State, R. (2020). A Data Science Approach for Honeypot Detection in Ethereum. In 2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC). Peer reviewed |
Camino, R. D., Hammerschmidt, C., & State, R. (17 July 2020). Working with Deep Generative Models and Tabular Data Imputation [Paper presentation]. First Workshop on the Art of Learning with Missing Values (Artemiss), Vienna, Austria. |
Camino, R. D., Hammerschmidt, C., & State, R. (2020). Minority Class Oversampling for Tabular Data with Deep Generative Models. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/43194. |
Camino, R. D., Hammerschmidt, C., & State, R. (2019). Improving Missing Data Imputation with Deep Generative Models. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/43196. |
Camino, R. D., Hammerschmidt, C., & State, R. (July 2018). Generating Multi-Categorical Samples with Generative Adversarial Networks [Paper presentation]. ICML 2018 workshop on Theoretical Foundations and Applications of Deep Generative Models, Stockholm, Sweden. |
Camino, R. D. (27 June 2018). GAN Applications with Discrete Data [Poster presentation]. 2nd Data Science Summer School (DS3), Paris, France. |
Falk, E., Camino, R. D., State, R., & Gurbani, V. K. (2017). On non-parametric models for detecting outages in the mobile network. In Integrated Network and Service Management 2017 (pp. 1139-1142). doi:10.23919/INM.2017.7987448 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 |