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2020 – today
- 2024
[c10]Anes Bendimerad, Romain Mathonat, Youcef Remil, Mehdi Kaytoue:
Exploiting Formal Concept Analysis for Data Modeling in Data Lakes. CONCEPTS 2024: 270-285- [c9]Youcef Remil
, Anes Bendimerad, Romain Mathonat, Chedy Raïssi, Mehdi Kaytoue:
DeepLSH: Deep Locality-Sensitive Hash Learning for Fast and Efficient Near-Duplicate Crash Report Detection. ICSE 2024: 198:1-198:12 - [i6]Youcef Remil, Anes Bendimerad, Romain Mathonat, Mehdi Kaytoue:
AIOps Solutions for Incident Management: Technical Guidelines and A Comprehensive Literature Review. CoRR abs/2404.01363 (2024) - [i5]Anes Bendimerad, Romain Mathonat, Youcef Remil, Mehdi Kaytoue:
Exploiting Formal Concept Analysis for Data Modeling in Data Lakes. CoRR abs/2408.13265 (2024) - 2023
- [c8]Youcef Remil, Anes Bendimerad, Mathieu Chambard, Romain Mathonat, Marc Plantevit, Mehdi Kaytoue:
Mining Java Memory Errors using Subjective Interesting Subgroups with Hierarchical Targets. ICDM (Workshops) 2023: 1221-1230 - [c7]Anes Bendimerad, Youcef Remil, Romain Mathonat, Mehdi Kaytoue:
On-Premise AIOps Infrastructure for a Software Editor SME: An Experience Report. ESEC/SIGSOFT FSE 2023: 1820-1831 - [d1]Romain Mathonat:
Rocket League Skillshots. UCI Machine Learning Repository, 2023
- [i4]Anes Bendimerad, Youcef Remil, Romain Mathonat, Mehdi Kaytoue:
On-Premise AIOps Infrastructure for a Software Editor SME: An Experience Report. CoRR abs/2308.11225 (2023) - [i3]Youcef Remil, Anes Bendimerad, Mathieu Chambard, Romain Mathonat, Marc Plantevit, Mehdi Kaytoue:
Mining Java Memory Errors using Subjective Interesting Subgroups with Hierarchical Targets. CoRR abs/2310.00781 (2023) - [i2]Youcef Remil, Anes Bendimerad, Romain Mathonat, Chedy Raïssi, Mehdi Kaytoue:
DeepLSH: Deep Locality-Sensitive Hash Learning for Fast and Efficient Near-Duplicate Crash Report Detection. CoRR abs/2310.06703 (2023) - 2021
- [j1]Romain Mathonat, Diana Nurbakova, Jean-François Boulicaut, Mehdi Kaytoue:
Anytime mining of sequential discriminative patterns in labeled sequences. Knowl. Inf. Syst. 63(2): 439-476 (2021) - [c6]Romain Mathonat, Diana Nurbakova, Jean-François Boulicaut, Mehdi Kaytoue:
Anytime Subgroup Discovery in High Dimensional Numerical Data. DSAA 2021: 1-10 - [c5]Youcef Remil, Anes Bendimerad, Romain Mathonat, Philippe Chaleat, Mehdi Kaytoue:
"What makes my queries slow?": Subgroup Discovery for SQL Workload Analysis. ASE 2021: 642-652 - [i1]Youcef Remil, Anes Bendimerad, Romain Mathonat, Philippe Chaleat, Mehdi Kaytoue:
"What makes my queries slow?": Subgroup Discovery for SQL Workload Analysis. CoRR abs/2108.03906 (2021) - 2020
- [b1]Romain Mathonat:
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). University of Lyon, France, 2020 - [c4]Romain Mathonat, Jean-François Boulicaut, Mehdi Kaytoue:
A Behavioral Pattern Mining Approach to Model Player Skills in Rocket League. CoG 2020: 267-274 - [c3]Alexandre Millot, Romain Mathonat, Rémy Cazabet, Jean-François Boulicaut:
Actionable Subgroup Discovery and Urban Farm Optimization. IDA 2020: 339-351
2010 – 2019
- 2019
- [c2]Romain Mathonat, Diana Nurbakova, Jean-François Boulicaut, Mehdi Kaytoue:
SeqScout: Using a Bandit Model to Discover Interesting Subgroups in Labeled Sequences. DSAA 2019: 81-90 - [c1]Romain Mathonat, Jean-François Boulicaut, Mehdi Kaytoue:
Découverte de sous-groupes à partir de données séquentielles par échantillonnage et optimisation locale. EGC 2019: 153-164
Coauthor Index
aka: Mehdi Kaytoue
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