Lorenzo Perini

32 papers A* 5A 2Journal 19Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Correction: TSelect: selecting relevant and non-redundant channels for multivariate time series classification. Data Min. Knowl. Discov. Loren Nuyts, Lorenzo Perini, Jesse Davis
2026	J	`jnl`	Dealing with Uncertainty in Contextual Anomaly Detection. Trans. Mach. Learn. Res. Luca Bindini, Lorenzo Perini, Stefano Nistri, Jesse Davis, Paolo Frasconi
2026	—	`conf`	MCGrad: Multicalibration at Web Scale. KDD (1) Niek Tax, Lorenzo Perini, Fridolin Linder, Daniel Haimovich, Dima Karamshuk, Nastaran Okati, Milan Vojnovic, Pavlos Athanasios Apostolopoulos
2026	J	`jnl`	On the Convergence of Multicalibration Gradient Boosting. CoRR Daniel Haimovich, Fridolin Linder, Lorenzo Perini, Niek Tax, Milan Vojnovic
2025	J	`jnl`	Dealing with Uncertainty in Contextual Anomaly Detection. CoRR Luca Bindini, Lorenzo Perini, Stefano Nistri, Jesse Davis, Paolo Frasconi
2025	J	`jnl`	MCGrad: Multicalibration at Web Scale. CoRR Lorenzo Perini, Daniel Haimovich, Fridolin Linder, Niek Tax, Dima Karamshuk, Milan Vojnovic, Nastaran Okati, Pavlos Athanasios Apostolopoulos
2025	J	`jnl`	Measuring multi-calibration. CoRR Ido Guy, Daniel Haimovich, Fridolin Linder, Nastaran Okati, Lorenzo Perini, Niek Tax, Mark Tygert
2025	J	`jnl`	Multicalibration yields better matchings. CoRR Riccardo Colini-Baldeschi, Simone Di Gregorio, Simone Fioravanti, Federico Fusco, Ido Guy, Daniel Haimovich, Stefano Leonardi, Fridolin Linder, Lorenzo Perini, Matteo Russo, Niek Tax
2025	J	`jnl`	Multiclass Local Calibration With the Jensen-Shannon Distance. CoRR Cesare Barbera, Lorenzo Perini, Giovanni De Toni, Andrea Passerini, Andrea Pugnana
2025	J	`jnl`	TSelect: selecting relevant and non-redundant channels for multivariate time series classification. Data Min. Knowl. Discov. Loren Nuyts, Lorenzo Perini, Jesse Davis
2025	J	`jnl`	Uncertainty-aware Evaluation of Auxiliary Anomalies with the Expected Anomaly Posterior. Trans. Mach. Learn. Res. Lorenzo Perini, Maja Rudolph, Sabrina Schmedding, Chen Qiu
2024	A	`conf`	Combining Active Learning and Learning to Reject for Anomaly Detection. ECAI Luca Stradiotti, Lorenzo Perini, Jesse Davis
2024	J	`jnl`	Deep Neural Network Benchmarks for Selective Classification. CoRR Andrea Pugnana, Lorenzo Perini, Jesse Davis, Salvatore Ruggieri
2024	J	`jnl`	Deep Neural Network Benchmarks for Selective Classification. J. Data-centric Mach. Learn. Res. Andrea Pugnana, Lorenzo Perini, Jesse Davis, Salvatore Ruggieri
2024	J	`jnl`	Investigating Mesa Structure Impact on C-V Measurements. IEEE Access Giovanna Sozzi, Giovanni Chiorboli, Lorenzo Perini, Roberta Nipoti
2024	J	`jnl`	Machine learning with a reject option: a survey. Mach. Learn. Kilian Hendrickx, Lorenzo Perini, Dries Van der Plas, Wannes Meert, Jesse Davis
2024	A	`conf`	Semi-Supervised Isolation Forest for Anomaly Detection. SDM Luca Stradiotti, Lorenzo Perini, Jesse Davis
2024	J	`jnl`	Uncertainty-aware Evaluation of Auxiliary Anomalies with the Expected Anomaly Posterior. CoRR Lorenzo Perini, Maja Rudolph, Sabrina Schmedding, Chen Qiu
2023	—	`conf`	Detecting Evasion Attacks in Deployed Tree Ensembles. ECML/PKDD (5) Laurens Devos, Lorenzo Perini, Wannes Meert, Jesse Davis
2023	A*	`conf`	Estimating the Contamination Factor's Distribution in Unsupervised Anomaly Detection. ICML Lorenzo Perini, Paul-Christian Bürkner, Arto Klami
2023	J	`jnl`	How to Allocate your Label Budget? Choosing between Active Learning and Learning to Reject in Anomaly Detection. CoRR Lorenzo Perini, Daniele Giannuzzi, Jesse Davis
2023	A*	`conf`	Learning from Positive and Unlabeled Multi-Instance Bags in Anomaly Detection. KDD Lorenzo Perini, Vincent Vercruyssen, Jesse Davis
2023	—	`conf`	Semi-supervised Learning from Active Noisy Soft Labels for Anomaly Detection. ECML/PKDD (1) Timo Martens, Lorenzo Perini, Jesse Davis
2023	A*	`conf`	Unsupervised Anomaly Detection with Rejection. NeurIPS Lorenzo Perini, Jesse Davis
2023	J	`jnl`	Unsupervised Anomaly Detection with Rejection. CoRR Lorenzo Perini, Jesse Davis
2022	J	`jnl`	Estimating the Contamination Factor's Distribution in Unsupervised Anomaly Detection. CoRR Lorenzo Perini, Paul C. Bürkner, Arto Klami
2022	—	`conf`	Multi-domain Active Learning for Semi-supervised Anomaly Detection. ECML/PKDD (4) Vincent Vercruyssen, Lorenzo Perini, Wannes Meert, Jesse Davis
2022	A*	`conf`	Transferring the Contamination Factor between Anomaly Detection Domains by Shape Similarity. AAAI Lorenzo Perini, Vincent Vercruyssen, Jesse Davis
2021	J	`jnl`	Machine Learning with a Reject Option: A survey. CoRR Kilian Hendrickx, Lorenzo Perini, Dries Van der Plas, Wannes Meert, Jesse Davis
2020	—	`conf`	A Ranking Stability Measure for Quantifying the Robustness of Anomaly Detection Methods. PKDD/ECML Workshops Lorenzo Perini, Connor Galvin, Vincent Vercruyssen
2020	A*	`conf`	Class Prior Estimation in Active Positive and Unlabeled Learning. IJCAI Lorenzo Perini, Vincent Vercruyssen, Jesse Davis
2020	—	`conf`	Quantifying the Confidence of Anomaly Detectors in Their Example-Wise Predictions. ECML/PKDD (3) Lorenzo Perini, Vincent Vercruyssen, Jesse Davis