Luca Ferragina

J. Intell. Inf. Syst., August, 2024

A Clustering-based Approach for Interpreting Black-box Models.

[BibT_eX]

[DOI]

Simona Nisticò

Proceedings of the 32nd Symposium of Advanced Database Systems, 2024

Indecision-Aware Deep Active Anomaly Detection.

[BibT_eX]

[DOI]

Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2024, 2024

2023

${{\mathrm {Latent}}Out}$: an unsupervised deep anomaly detection approach exploiting latent space distribution.

[BibT_eX]

[DOI]

Mach. Learn., November, 2023

Reconstruction Error-based Anomaly Detection with Few Outlying Examples.

[BibT_eX]

[DOI]

CoRR, 2023

2022

Detecting Anomalies with rmLatentOut: Novel Scores, Architectures, and Settings.

[BibT_eX]

[DOI]

Proceedings of the Foundations of Intelligent Systems - 26th International Symposium, 2022

Cooperative Deep Unsupervised Anomaly Detection.

[BibT_eX]

[DOI]

Proceedings of the Discovery Science - 25th International Conference, 2022

2021

Meta-feature Extraction Strategies for Active Anomaly Detection.

[BibT_eX]

[DOI]

Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2021, 2021

2020

Improving Deep Unsupervised Anomaly Detection by Exploiting VAE Latent Space Distribution.

[BibT_eX]

[DOI]