Romain Mathonat

According to our database, Romain Mathonat authored at least 11 papers between 2019 and 2023.

Collaborative distances:

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

2023

DeepLSH: Deep Locality-Sensitive Hash Learning for Fast and Efficient Near-Duplicate Crash Report Detection.

Youcef Remil, Anes Bendimerad, Romain Mathonat, Chedy Raïssi, Mehdi Kaytoue

CoRR, 2023

On-Premise AIOps Infrastructure for a Software Editor SME: An Experience Report.

Anes Bendimerad, Youcef Remil, Romain Mathonat, Mehdi Kaytoue

Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2023

Mining Java Memory Errors using Subjective Interesting Subgroups with Hierarchical Targets.

Youcef Remil, Anes Bendimerad, Mathieu Chambard, Romain Mathonat, Marc Plantevit, Mehdi Kaytoue

Proceedings of the IEEE International Conference on Data Mining, 2023

2021

Anytime mining of sequential discriminative patterns in labeled sequences.

Romain Mathonat, Diana Nurbakova, Jean-François Boulicaut, Mehdi Kaytoue

Knowl. Inf. Syst., 2021

"What makes my queries slow?": Subgroup Discovery for SQL Workload Analysis.

Youcef Remil, Anes Bendimerad, Romain Mathonat, Philippe Chaleat, Mehdi Kaytoue

Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering, 2021

Anytime Subgroup Discovery in High Dimensional Numerical Data.

Romain Mathonat, Diana Nurbakova, Jean-François Boulicaut, Mehdi Kaytoue

Proceedings of the 8th IEEE International Conference on Data Science and Advanced Analytics, 2021

2020

Rule Discovery in Labeled Sequential Data: Application to Game Analytics. (Découverte de règles pour séquences labélisées: application à l'analyse de données de jeux vidéos).

Romain Mathonat

PhD thesis, 2020

Actionable Subgroup Discovery and Urban Farm Optimization.

Alexandre Millot, Romain Mathonat, Rémy Cazabet, Jean-François Boulicaut

Proceedings of the Advances in Intelligent Data Analysis XVIII, 2020

A Behavioral Pattern Mining Approach to Model Player Skills in Rocket League.

Romain Mathonat, Jean-François Boulicaut, Mehdi Kaytoue

Proceedings of the IEEE Conference on Games, 2020

2019

Découverte de sous-groupes à partir de données séquentielles par échantillonnage et optimisation locale.

Romain Mathonat, Jean-François Boulicaut, Mehdi Kaytoue

Proceedings of the Extraction et Gestion des connaissances, 2019

SeqScout: Using a Bandit Model to Discover Interesting Subgroups in Labeled Sequences.

Romain Mathonat, Diana Nurbakova, Jean-François Boulicaut, Mehdi Kaytoue

Proceedings of the 2019 IEEE International Conference on Data Science and Advanced Analytics, 2019