Michele Linardi

According to our database, Michele Linardi authored at least 18 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Analysis of Socially Unacceptable Discourse with Zero-shot Learning.

Rayane Ghilene, Dimitra Niaouri, Michele Linardi, Julien Longhi

CoRR, 2024

2023

Correction to: Unsupervised and scalable subsequence anomaly detection in large data series.

Paul Boniol, Michele Linardi, Federico Roncallo, Themis Palpanas, Mohammed Meftah, Emmanuel Remy

VLDB J., March, 2023

Studying Socially Unacceptable Discourse Classification (SUD) through different eyes: "Are we on the same page ?".

Bruno Machado Carneiro, Michele Linardi, Julien Longhi

CoRR, 2023

Towards Explainable AI4EO: An Explainable Deep Learning Approach for Crop Type Mapping using Satellite Images Time Series.

Adel Abbas, Michele Linardi, Etienne Vareille, Vassillis Christophides, Claudia Paris

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

Evaluating Explanation Methods of Multivariate Time Series Classification through Causal Lenses.

Etienne Vareille, Adel Abbas, Michele Linardi, Vassillis Christophides

Proceedings of the 10th IEEE International Conference on Data Science and Advanced Analytics, 2023

2021

Unsupervised and scalable subsequence anomaly detection in large data series.

Paul Boniol, Michele Linardi, Federico Roncallo, Themis Palpanas, Mohammed Meftah, Emmanuel Remy

VLDB J., 2021

2020

Scalable data series subsequence matching with ULISSE.

Michele Linardi, Themis Palpanas

VLDB J., 2020

Matrix profile goes MAD: variable-length motif and discord discovery in data series.

Michele Linardi, Yan Zhu, Themis Palpanas, Eamonn J. Keogh

Data Min. Knowl. Discov., 2020

Automated Anomaly Detection in Large Sequences.

Paul Boniol, Michele Linardi, Federico Roncallo, Themis Palpanas

Proceedings of the 36th IEEE International Conference on Data Engineering, 2020

SAD: An Unsupervised System for Subsequence Anomaly Detection.

Paul Boniol, Michele Linardi, Federico Roncallo, Themis Palpanas

Proceedings of the 36th IEEE International Conference on Data Engineering, 2020

2019

Variable-length similarity search for very large data series: subsequence matching, motif and discord detection. (Recherche de similarité de longueur variable pour l'analyse de grandes séries temporelles: appariement de séquences, recherche de motifs et anomalies).

Michele Linardi

PhD thesis, 2019

Effective and Efficient Variable-Length Data Series Analytics.

Michele Linardi

Proceedings of the VLDB 2019 PhD Workshop, 2019

2018

Scalable, Variable-Length Similarity Search in Data Series: The ULISSE Approach.

Michele Linardi, Themis Palpanas

Proc. VLDB Endow., 2018

VALMOD: A Suite for Easy and Exact Detection of Variable Length Motifs in Data Series.

Michele Linardi, Yan Zhu, Themis Palpanas, Eamonn J. Keogh

Proceedings of the 2018 International Conference on Management of Data, 2018

Matrix Profile X: VALMOD - Scalable Discovery of Variable-Length Motifs in Data Series.

Michele Linardi, Yan Zhu, Themis Palpanas, Eamonn J. Keogh

Proceedings of the 2018 International Conference on Management of Data, 2018

ULISSE: ULtra Compact Index for Variable-Length Similarity Search in Data Series.

Michele Linardi, Themis Palpanas

Proceedings of the 34th IEEE International Conference on Data Engineering, 2018

2017

ChaseFUN: a Data Exchange Engine for Functional Dependencies at Scale.

Angela Bonifati, Ioana Ileana, Michele Linardi

Proceedings of the 20th International Conference on Extending Database Technology, 2017

2016

Functional Dependencies Unleashed for Scalable Data Exchange.

Angela Bonifati, Ioana Ileana, Michele Linardi

Proceedings of the 28th International Conference on Scientific and Statistical Database Management, 2016