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- Simone Amirato, Fabrizio Angiulli, Fabio Fassetti, Luca Ferragina (2024). Indecision-Aware Deep Active Anomaly Detection. Intelligent Data Engineering and Automated Learning (IDEAL2024).
- Fabrizio Angiulli, Fabio Fassetti, Luca Ferragina (2024). Enhancing Anomaly Detector with LatentOut. Journal of Intelligent Information Systems.
- Luca Ferragina, Simona Nisticò (2024). A Clustering-based Approach for Interpreting Black-box Models. Proceedings of the 32nd Symposium on Advanced Database Systems (SEBD2024).
- Fabrizio Angiulli, Fabio Fassetti, Luca Ferragina (2023). Reconstruction Error-based Anomaly Detection with Few Outlying Examples. Preprint.
- Fabrizio Angiulli, Fabio Fassetti, Luca Ferragina, Rosaria Spada (2022). Cooperative Deep Unsupervised Anomaly Detection. Proceedings of 25th International Conference on Discovery Science (DS2022).
- Fabrizio Angiulli, Fabio Fassetti, Luca Ferragina (2022). Detecting Anomalies with LatentOut: Novel Scores, Architectures, and Settings. Proceedings of 26th International Symposium on Methodologies for Intelligent Systems (ISMIS2022).
- Fabrizio Angiulli, Fabio Fassetti, Luca Ferragina (2022). LatentOut: an unsupervised deep anomaly detection approach exploiting latent space distribution. Machine Learning.
- Fabrizio Angiulli, Fabio Fassetti, Luca Ferragina, Prospero Papaleo (2021). Meta-feature Extraction Strategies for Active Anomaly Detection. Proceedings of 22nd Intelligent Data Engineering and Automated Learning (IDEAL2021).
- Fabrizio Angiulli, Fabio Fassetti, Luca Ferragina (2020). Improving deep unsupervised anomaly detection by exploiting VAE latent space distribution. Proceedings of 23rd International Conference on Discovery Science (DS2020).