| Matrix profile X: VALMOD-scalable discovery of variable-length motifs in data series M Linardi, Y Zhu, T Palpanas, E Keogh Proceedings of the 2018 international conference on management of data, 1053 …, 2018 | 105 | 2018 |
| Matrix profile goes MAD: variable-length motif and discord discovery in data series M Linardi, Y Zhu, T Palpanas, E Keogh Data Mining and Knowledge Discovery 34, 1022-1071, 2020 | 65 | 2020 |
| Automated anomaly detection in large sequences P Boniol, M Linardi, F Roncallo, T Palpanas 2020 IEEE 36th international conference on data engineering (ICDE), 1834-1837, 2020 | 61 | 2020 |
| Scalable, variable-length similarity search in data series: The ULISSE approach M Linardi, T Palpanas Proceedings of the VLDB Endowment 11 (13), 2236-2248, 2018 | 59 | 2018 |
| Unsupervised and scalable subsequence anomaly detection in large data series P Boniol, M Linardi, F Roncallo, T Palpanas, M Meftah, E Remy The VLDB Journal 30 (6), 909-931, 2021 | 55 | 2021 |
| VALMOD: A suite for easy and exact detection of variable length motifs in data series M Linardi, Y Zhu, T Palpanas, E Keogh Proceedings of the 2018 International Conference on Management of Data, 1757 …, 2018 | 30 | 2018 |
| Ulisse: Ultra compact index for variable-length similarity search in data series M Linardi, T Palpanas 2018 IEEE 34th International Conference on Data Engineering (ICDE), 1356-1359, 2018 | 30 | 2018 |
| Scalable data series subsequence matching with ULISSE M Linardi, T Palpanas The VLDB Journal 29 (6), 1449-1474, 2020 | 25 | 2020 |
| Functional dependencies unleashed for scalable data exchange A Bonifati, I Ileana, M Linardi Proceedings of the 28th International Conference on Scientific and …, 2016 | 24 | 2016 |
| SAD: an unsupervised system for subsequence anomaly detection P Boniol, M Linardi, F Roncallo, T Palpanas 2020 IEEE 36th International Conference on Data Engineering (ICDE), 1778-1781, 2020 | 21 | 2020 |
| ChaseFUN: a Data Exchange Engine for Functional Dependencies at Scale. A Bonifati, I Ileana, M Linardi EDBT, 534-537, 2017 | 6 | 2017 |
| Studying Socially Unacceptable Discourse Classification (SUD) through different eyes:" Are we on the same page?" BM Carneiro, M Linardi, J Longhi arXiv preprint arXiv:2308.04180, 2023 | 4 | 2023 |
| Towards explainable ai4eo: An explainable deep learning approach for crop type mapping using satellite images time series A Abbas, M Linardi, E Vareille, V Christophides, C Paris IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium …, 2023 | 3 | 2023 |
| Evaluating Explanation Methods of Multivariate Time Series Classification through Causal Lenses E Vareille, A Abbas, M Linardi, V Christophides 2023 IEEE 10th International Conference on Data Science and Advanced …, 2023 | 2 | 2023 |
| Correction to: Unsupervised and scalable subsequence anomaly detection in large data series. P Boniol, M Linardi, F Roncallo, T Palpanas, M Meftah, E Remy VLDB J. 32 (2), 469, 2023 | 2 | 2023 |
| Effective and efficient variable-length data series analytics M Linardi arXiv preprint arXiv:2009.11648, 2020 | 2 | 2020 |
| Analysis of Socially Unacceptable Discourse with Zero-shot Learning R Ghilene, D Niaouri, M Linardi, J Longhi arXiv preprint arXiv:2409.13735, 2024 | | 2024 |
| Studying Socially Unacceptable Discourse Classification (SUD) through different eyes:" Are we on the same page?" B Machado Carneiro, M Linardi, J Longhi arXiv e-prints, arXiv: 2308.04180, 2023 | | 2023 |
| Determination of health status of systems equipped with sensors T Palpanas, M Linardi, P Boniol, F Roncallo, M Meftah, R Emmanuel US Patent 11,471,113, 2022 | | 2022 |
| Unsupervised Time Series Anomaly Detection: The Road to Effective Explainability M Linardi, V Christophides Extraction et Gestion des Connaissances: EGC'2022, 2022 | | 2022 |
Themis PalpanasDistinguished Professor, University Paris Cite, French University Institute (IUF)Verified email at mi.parisdescartes.fr
