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Lorenzo Perini

About Lorenzo Perini

Lorenzo Perini, With an exceptional h-index of 7 and a recent h-index of 7 (since 2020), a distinguished researcher at Katholieke Universiteit Leuven, specializes in the field of Anomaly Detection, Uncertainty Quantification, PU Learning, Active Learning, Learning to Reject.

His recent articles reflect a diverse array of research interests and contributions to the field:

Deep Neural Network Benchmarks for Selective Classification

Semi-Supervised Isolation Forest for Anomaly Detection

Machine learning with a reject option: A survey

Operational, Uncertainty-Aware, and Reliable Anomaly Detection

Unsupervised anomaly detection with rejection

Detecting Evasion Attacks in Deployed Tree Ensembles

Semi-supervised Learning from Active Noisy Soft Labels for Anomaly Detection

Learning from Positive and Unlabeled Multi-Instance Bags in Anomaly Detection

Lorenzo Perini Information

University

Position

PhD Student in Machine Learning

Citations(all)

161

Citations(since 2020)

161

Cited By

2

hIndex(all)

7

hIndex(since 2020)

7

i10Index(all)

6

i10Index(since 2020)

6

Email

University Profile Page

Google Scholar

Lorenzo Perini Skills & Research Interests

Anomaly Detection

Uncertainty Quantification

PU Learning

Active Learning

Learning to Reject

Top articles of Lorenzo Perini

Deep Neural Network Benchmarks for Selective Classification

arXiv preprint arXiv:2401.12708

2024/1/23

Lorenzo Perini
Lorenzo Perini

H-Index: 1

Jesse Davis
Jesse Davis

H-Index: 24

Semi-Supervised Isolation Forest for Anomaly Detection

2024

Lorenzo Perini
Lorenzo Perini

H-Index: 1

Jesse Davis
Jesse Davis

H-Index: 24

Machine learning with a reject option: A survey

Machine Learning

2024/3/29

Kilian Hendrickx
Kilian Hendrickx

H-Index: 2

Lorenzo Perini
Lorenzo Perini

H-Index: 1

Wannes Meert
Wannes Meert

H-Index: 20

Jesse Davis
Jesse Davis

H-Index: 24

Operational, Uncertainty-Aware, and Reliable Anomaly Detection

2024/3/28

Lorenzo Perini
Lorenzo Perini

H-Index: 1

Unsupervised anomaly detection with rejection

Advances in Neural Information Processing Systems

2024/2/13

Lorenzo Perini
Lorenzo Perini

H-Index: 1

Jesse Davis
Jesse Davis

H-Index: 24

Detecting Evasion Attacks in Deployed Tree Ensembles

2023/9/18

Laurens Devos
Laurens Devos

H-Index: 2

Lorenzo Perini
Lorenzo Perini

H-Index: 1

Wannes Meert
Wannes Meert

H-Index: 20

Jesse Davis
Jesse Davis

H-Index: 24

Semi-supervised Learning from Active Noisy Soft Labels for Anomaly Detection

2023/9/17

Lorenzo Perini
Lorenzo Perini

H-Index: 1

Jesse Davis
Jesse Davis

H-Index: 24

Learning from Positive and Unlabeled Multi-Instance Bags in Anomaly Detection

2023/8/6

Lorenzo Perini
Lorenzo Perini

H-Index: 1

Vincent Vercruyssen
Vincent Vercruyssen

H-Index: 4

Jesse Davis
Jesse Davis

H-Index: 24

Estimating the contamination factor’s distribution in unsupervised anomaly detection

2023/7/3

Lorenzo Perini
Lorenzo Perini

H-Index: 1

Arto Klami
Arto Klami

H-Index: 18

How to allocate your label budget? choosing between active learning and learning to reject in anomaly detection

arXiv preprint arXiv:2301.02909

2023/1/7

Lorenzo Perini
Lorenzo Perini

H-Index: 1

Jesse Davis
Jesse Davis

H-Index: 24

Multi-domain active learning for semi-supervised anomaly detection

2022/9/19

Vincent Vercruyssen
Vincent Vercruyssen

H-Index: 4

Lorenzo Perini
Lorenzo Perini

H-Index: 1

Wannes Meert
Wannes Meert

H-Index: 20

Jesse Davis
Jesse Davis

H-Index: 24

Transferring the contamination factor between anomaly detection domains by shape similarity

Proceedings of the AAAI Conference on Artificial Intelligence

2022/6/28

Lorenzo Perini
Lorenzo Perini

H-Index: 1

Vincent Vercruyssen
Vincent Vercruyssen

H-Index: 4

Jesse Davis
Jesse Davis

H-Index: 24

The effect of hyperparameter tuning on the comparative evaluation of unsupervised anomaly detection methods

Proceedings of the KDD'21 Workshop on Outlier Detection and Description

2021/8/15

Jonas Soenen
Jonas Soenen

H-Index: 0

Elia Van Wolputte
Elia Van Wolputte

H-Index: 4

Lorenzo Perini
Lorenzo Perini

H-Index: 1

Vincent Vercruyssen
Vincent Vercruyssen

H-Index: 4

Wannes Meert
Wannes Meert

H-Index: 20

Jesse Davis
Jesse Davis

H-Index: 24

Hendrik Blockeel
Hendrik Blockeel

H-Index: 19

A ranking stability measure for quantifying the robustness of anomaly detection methods

2020

Lorenzo Perini
Lorenzo Perini

H-Index: 1

Vincent Vercruyssen
Vincent Vercruyssen

H-Index: 4

Quantifying the confidence of anomaly detectors in their example-wise predictions

2020/9/14

Lorenzo Perini
Lorenzo Perini

H-Index: 1

Vincent Vercruyssen
Vincent Vercruyssen

H-Index: 4

Jesse Davis
Jesse Davis

H-Index: 24

Class prior estimation in active positive and unlabeled learning

Proceedings of the 29th international joint conference on artificial intelligence and the 17th pacific rim international conference on artificial intelligence (ijcai-pricai 2020)

2020/1/1

Lorenzo Perini
Lorenzo Perini

H-Index: 1

Vincent Vercruyssen
Vincent Vercruyssen

H-Index: 4

Jesse Davis
Jesse Davis

H-Index: 24

See List of Professors in Lorenzo Perini University(Katholieke Universiteit Leuven)

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