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ORCIDJulie Jacques
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- affiliation: Lille University of Science and Technology, France
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Books and Theses
- 2013
[b1]Julie Jacques:
Classification sur données médicales à l'aide de méthodes d'optimisation et de datamining, appliquée au pré-screening dans les essais cliniques. (Classification of medical data using optimization methods applied to patient screening in clinical trials.). Lille University of Science and Technology, France, 2013
Journal Articles
- 2025
- [j6]Mounir Hafsa
, Pamela Wattebled, Julie Jacques, Laetitia Jourdan:
Solving a multiobjective professional timetabling problem using evolutionary algorithms at Mandarine Academy. Int. Trans. Oper. Res. 32(1): 244-269 (2025) - 2024
- [j5]Adán José García, Julie Jacques, Vincent Sobanski, Clarisse Dhaenens:
Metaheuristic Biclustering Algorithms: From State-of-the-art to Future Opportunities. ACM Comput. Surv. 56(3): 69:1-69:38 (2024) - 2022
- [j4]Maxence Vandromme, Julie Jacques, Julien Taillard, Laetitia Jourdan, Clarisse Dhaenens:
A Biclustering Method for Heterogeneous and Temporal Medical Data. IEEE Trans. Knowl. Data Eng. 34(2): 506-518 (2022) - 2020
- [j3]Julie Jacques, Hélène Martin-Huyghe, Justine Lemtiri-Florek, Julien Taillard, Laetitia Jourdan, Clarisse Dhaenens, David Delerue, Arnaud Hansske, Valérie Leclercq:
The detection of hospitalized patients at risk of testing positive to multi-drug resistant bacteria using MOCA-I, a rule-based "white-box" classification algorithm for medical data. Int. J. Medical Informatics 142: 104242 (2020) - 2017
- [j2]Maxence Vandromme, Julie Jacques, Julien Taillard, Arnaud Hansske, Laetitia Vermeulen-Jourdan, Clarisse Dhaenens:
Extraction and optimization of classification rules for temporal sequences: Application to hospital data. Knowl. Based Syst. 122: 148-158 (2017) - 2015
- [j1]Julie Jacques, Julien Taillard, David Delerue, Clarisse Dhaenens, Laetitia Jourdan:
Conception of a dominance-based multi-objective local search in the context of classification rule mining in large and imbalanced data sets. Appl. Soft Comput. 34: 705-720 (2015)
Conference and Workshop Papers
- 2024
- [c15]Julie Jacques, Alexander Bassett:
Extracting White-Box Knowledge from Word Embedding: Modeling as an Optimization Problem. MIC (1) 2024: 178-183 - [c14]Adán José García, Julie Jacques, Clément Chauvet, Vincent Sobanski, Clarisse Dhaenens:
HBIC: A Biclustering Algorithm for Heterogeneous Datasets. ECAI 2024: 3088-3095 - 2023
- [c13]Meyssa Zouambi, Clarisse Dhaenens, Julie Jacques:
An Alternative Pareto-Based Approach to Multi-Objective Neural Architecture Search. CEC 2023: 1-8 - 2022
- [c12]Mounir Hafsa, Pamela Wattebled, Julie Jacques, Laetitia Jourdan:
Multi-objective recommender system for corporate MOOC. GECCO Companion 2022: 2314-2317 - [c11]Meyssa Zouambi, Julie Jacques, Clarisse Dhaenens:
LS-PON: A Prediction-Based Local Search for Neural Architecture Search. LOD (1) 2022: 108-122 - [c10]Adán José García, Julie Jacques, Alexandre Filiot, Julia Handl, David Launay, Vincent Sobanski, Clarisse Dhaenens:
Multi-view Clustering of Heterogeneous Health Data: Application to Systemic Sclerosis. PPSN (2) 2022: 352-367 - [c9]Mounir Hafsa, Pamela Wattebled, Julie Jacques, Laetitia Jourdan:
A Multi-Objective E-learning Recommender System at Mandarine Academy. MORS@RecSys 2022 - 2021
- [c8]Mounir Hafsa, Pamela Wattebled, Julie Jacques, Laetitia Jourdan:
A Multi-Objective Evolutionary Approach to Professional Course Timetabling: A Real-World Case Study. CEC 2021: 997-1004 - 2020
- [c7]Sara Tari, Nicolas Szczepanski, Lucien Mousin, Julie Jacques, Marie-Eléonore Kessaci, Laetitia Jourdan:
Multi-objective Automatic Algorithm Configuration for the Classification Problem of Imbalanced Data. CEC 2020: 1-8 - [c6]Sara Tari, Lucien Mousin, Julie Jacques, Marie-Eléonore Kessaci, Laetitia Jourdan:
Impact of the Discretization of VOCs for Cancer Prediction Using a Multi-Objective Algorithm. LION 2020: 151-157 - [c5]Sara Tari, Holger H. Hoos, Julie Jacques, Marie-Eléonore Kessaci, Laetitia Jourdan:
Automatic Configuration of a Multi-objective Local Search for Imbalanced Classification. PPSN (1) 2020: 65-77 - 2016
- [c4]Maxence Vandromme, Julie Jacques, Julien Taillard, Laetitia Jourdan, Clarisse Dhaenens:
A Scalable Biclustering Method for Heterogeneous Medical Data. MOD 2016: 70-81 - 2013
- [c3]Julie Jacques, Julien Taillard, David Delerue, Laetitia Jourdan, Clarisse Dhaenens:
The benefits of using multi-objectivization for mining pittsburgh partial classification rules in imbalanced and discrete data. GECCO 2013: 543-550 - [c2]Julie Jacques, Julien Taillard, David Delerue, Laetitia Jourdan, Clarisse Dhaenens:
MOCA-I: Discovering Rules and Guiding Decision Maker in the Context of Partial Classification in Large and Imbalanced Datasets. LION 2013: 37-51 - 2012
- [c1]Pascal Van Hille, Julie Jacques, Julien Taillard, Arnaud Rosier, David Delerue, Anita Burgun, Olivier Dameron:
Comparing Drools and ontology reasoning approaches for telecardiology decision support. MIE 2012: 300-304
Parts in Books or Collections
- 2015
- [p1]Julie Hamon, Julie Jacques, Laetitia Jourdan, Clarisse Dhaenens:
Knowledge Discovery in Bioinformatics. Handbook of Computational Intelligence 2015: 1211-1223
Informal and Other Publications
- 2024
- [i2]Adán José García, Julie Jacques, Clément Chauvet, Vincent Sobanski, Clarisse Dhaenens:
HBIC: A Biclustering Algorithm for Heterogeneous Datasets. CoRR abs/2408.13217 (2024) - 2022
- [i1]Adán José García, Julie Jacques, Vincent Sobanski, Clarisse Dhaenens:
Biclustering Algorithms Based on Metaheuristics: A Review. CoRR abs/2203.16241 (2022)
Coauthor Index
aka: Laetitia Jourdan
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