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Michele Linardi
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2020 – today
- 2024
- [i7]Rayane Ghilene, Dimitra Niaouri, Michele Linardi, Julien Longhi:
Analysis of Socially Unacceptable Discourse with Zero-shot Learning. CoRR abs/2409.13735 (2024) - 2023
- [j5]Paul Boniol
, Michele Linardi, Federico Roncallo, Themis Palpanas, Mohammed Meftah, Emmanuel Remy:
Correction to: Unsupervised and scalable subsequence anomaly detection in large data series. VLDB J. 32(2): 469 (2023) - [c10]Etienne Vareille, Adel Abbas, Michele Linardi, Vassillis Christophides:
Evaluating Explanation Methods of Multivariate Time Series Classification through Causal Lenses. DSAA 2023: 1-10 - [c9]Adel Abbas, Michele Linardi, Etienne Vareille, Vassillis Christophides, Claudia Paris
Towards Explainable AI4EO: An Explainable Deep Learning Approach for Crop Type Mapping using Satellite Images Time Series. IGARSS 2023: 1088-1091 - [i6]Bruno Machado Carneiro, Michele Linardi, Julien Longhi:
Studying Socially Unacceptable Discourse Classification (SUD) through different eyes: "Are we on the same page ?". CoRR abs/2308.04180 (2023) - 2021
- [j4]Paul Boniol
Unsupervised and scalable subsequence anomaly detection in large data series. VLDB J. 30(6): 909-931 (2021) - 2020
- [j3]Michele Linardi
Matrix profile goes MAD: variable-length motif and discord discovery in data series. Data Min. Knowl. Discov. 34(4): 1022-1071 (2020) - [j2]Michele Linardi
Scalable data series subsequence matching with ULISSE. VLDB J. 29(6): 1449-1474 (2020) - [c8]Paul Boniol, Michele Linardi
SAD: An Unsupervised System for Subsequence Anomaly Detection. ICDE 2020: 1778-1781 - [c7]Paul Boniol, Michele Linardi
Automated Anomaly Detection in Large Sequences. ICDE 2020: 1834-1837 - [i5]Michele Linardi, Yan Zhu, Themis Palpanas, Eamonn J. Keogh:
VALMOD: A Suite for Easy and Exact Detection of Variable Length Motifs in Data Series. CoRR abs/2008.13432 (2020) - [i4]Michele Linardi, Yan Zhu, Themis Palpanas, Eamonn J. Keogh:
Matrix Profile Goes MAD: Variable-Length Motif And Discord Discovery in Data Series. CoRR abs/2008.13447 (2020) - [i3]Michele Linardi, Themis Palpanas:
Scalable Data Series Subsequence Matching with ULISSE. CoRR abs/2009.10373 (2020) - [i2]Michele Linardi:
Effective and Efficient Variable-Length Data Series Analytics. CoRR abs/2009.11648 (2020)
2010 – 2019
- 2019
- [b1]Michele Linardi:
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). Sorbonne Paris Cité, France, 2019 - [c6]Michele Linardi:
Effective and Efficient Variable-Length Data Series Analytics. PhD@VLDB 2019 - 2018
- [j1]Michele Linardi
Scalable, Variable-Length Similarity Search in Data Series: The ULISSE Approach. Proc. VLDB Endow. 11(13): 2236-2248 (2018) - [c5]Michele Linardi
ULISSE: ULtra Compact Index for Variable-Length Similarity Search in Data Series. ICDE 2018: 1356-1359 - [c4]Michele Linardi
Matrix Profile X: VALMOD - Scalable Discovery of Variable-Length Motifs in Data Series. SIGMOD Conference 2018: 1053-1066 - [c3]Michele Linardi
VALMOD: A Suite for Easy and Exact Detection of Variable Length Motifs in Data Series. SIGMOD Conference 2018: 1757-1760 - 2017
- [c2]Angela Bonifati
ChaseFUN: a Data Exchange Engine for Functional Dependencies at Scale. EDBT 2017: 534-537 - 2016
- [c1]Angela Bonifati
Functional Dependencies Unleashed for Scalable Data Exchange. SSDBM 2016: 2:1-2:12 - [i1]Angela Bonifati, Ioana Ileana, Michele Linardi:
Functional Dependencies Unleashed for Scalable Data Exchange. CoRR abs/1602.00563 (2016)
Coauthor Index
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