Paul Boniol

According to our database, Paul Boniol authored at least 19 papers between 2020 and 2024.

Collaborative distances:

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

2024

Arm-CODA: A Data Set of Upper-limb Human Movement During Routine Examination.

Sylvain W. Combettes, Paul Boniol, Antoine Mazarguil, Danping Wang, Diego Vaquero-Ramos, Marion Chauveau, Laurent Oudre, Nicolas Vayatis, Pierre-Paul Vidal, Alexandra Roren, Marie-Martine Lefèvre-Colau

Image Process. Line, 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

Choose Wisely: An Extensive Evaluation of Model Selection for Anomaly Detection in Time Series.

Emmanouil Sylligardos, Paul Boniol, John Paparrizos, Panos E. Trahanias, Themis Palpanas

Proc. VLDB Endow., 2023

Appliance Detection Using Very Low-Frequency Smart Meter Time Series.

Adrien Petralia, Philippe Charpentier, Paul Boniol, Themis Palpanas

Proceedings of the 14th ACM International Conference on Future Energy Systems, 2023

New Trends in Time Series Anomaly Detection.

Paul Boniol, John Paparrizos, Themis Palpanas

Proceedings of the Proceedings 26th International Conference on Extending Database Technology, 2023

2022

TSB-UAD: An End-to-End Benchmark Suite for Univariate Time-Series Anomaly Detection.

John Paparrizos, Yuhao Kang, Paul Boniol, Ruey S. Tsay, Themis Palpanas, Michael J. Franklin

Proc. VLDB Endow., 2022

Volume Under the Surface: A New Accuracy Evaluation Measure for Time-Series Anomaly Detection.

John Paparrizos, Paul Boniol, Themis Palpanas, Ruey Tsay, Aaron J. Elmore, Michael J. Franklin

Proc. VLDB Endow., 2022

Theseus: Navigating the Labyrinth of Time-Series Anomaly Detection.

Paul Boniol, John Paparrizos, Yuhao Kang, Themis Palpanas, Ruey S. Tsay, Aaron J. Elmore, Michael J. Franklin

Proc. VLDB Endow., 2022

dCAM: Dimension-wise Class Activation Map for Explaining Multivariate Data Series Classification.

Paul Boniol, Mohammed Meftah, Emmanuel Remy, Themis Palpanas

Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

2021

Detection of anomalies and identification of their precursors in large data series collections. (Détection d'anomalies et identification de leurs précurseurs dans des grandes collections de séries temporelles).

Paul Boniol

PhD thesis, 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

SAND in Action: Subsequence Anomaly Detection for Streams.

Paul Boniol, John Paparrizos, Themis Palpanas, Michael J. Franklin

Proc. VLDB Endow., 2021

SAND: Streaming Subsequence Anomaly Detection.

Paul Boniol, John Paparrizos, Themis Palpanas, Michael J. Franklin

Proc. VLDB Endow., 2021

2020

GraphAn: Graph-based Subsequence Anomaly Detection.

Paul Boniol, Themis Palpanas, Mohammed Meftah, Emmanuel Remy

Proc. VLDB Endow., 2020

Series2Graph: Graph-based Subsequence Anomaly Detection for Time Series.

Paul Boniol, Themis Palpanas

Proc. VLDB Endow., 2020

Unsupervised Subsequence Anomaly Detection in Large Sequences.

Paul Boniol

Proceedings of the VLDB 2020 PhD Workshop co-located with the 46th International Conference on Very Large Databases (VLDB 2020), ONLINE, August 31, 2020

Performance in the Courtroom: Automated Processing and Visualization of Appeal Court Decisions in France.

Paul Boniol, George Panagopoulos, Christos Xypolopoulos, Rajaa El Hamdani, David Restrepo Amariles, Michalis Vazirgiannis

Proceedings of the Natural Legal Language Processing Workshop 2020 co-located with the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2020), 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