• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 74 matches

• 2024
• 
  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)
• 
  Julien Baste, Antoine Castillon, Clarisse Dhaenens, Mohammed Haddad, Hamida Seba:
  γ-clustering problems: Classical and parametrized complexity. Theor. Comput. Sci. 1018: 114784 (2024)
• 
  Adán José García, Julie Jacques, Clément Chauvet, Vincent Sobanski, Clarisse Dhaenens:
  HBIC: A Biclustering Algorithm for Heterogeneous Datasets. ECAI 2024: 3088-3095
• 
  Adán José García, Julie Jacques, Clément Chauvet, Vincent Sobanski, Clarisse Dhaenens:
  HBIC: A Biclustering Algorithm for Heterogeneous Datasets. CoRR abs/2408.13217 (2024)
• 2023
• 
  Meyssa Zouambi, Clarisse Dhaenens, Julie Jacques:
  An Alternative Pareto-Based Approach to Multi-Objective Neural Architecture Search. CEC 2023: 1-8
• 2022
• 
  Clarisse Dhaenens, Laetitia Jourdan:
  Metaheuristics for data mining: survey and opportunities for big data. Ann. Oper. Res. 314(1): 117-140 (2022)
• 
  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)
• 
  Meyssa Zouambi, Julie Jacques, Clarisse Dhaenens:
  LS-PON: A Prediction-Based Local Search for Neural Architecture Search. LOD (1) 2022: 108-122
• 
  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
• 
  Adán José García, Julie Jacques, Vincent Sobanski, Clarisse Dhaenens:
  Biclustering Algorithms Based on Metaheuristics: A Review. CoRR abs/2203.16241 (2022)
• 2020
• 
  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)
• 
  Rabin Kumar Sahu, Clarisse Dhaenens, Nadarajen Veerapen, Manuel Davy:
  An Approximate Method for Integrated Stochastic Replenishment Planning with Supplier Selection. ICORES 2020: 80-88
• 2019
• 
  Clarisse Dhaenens, Laetitia Jourdan:
  Metaheuristics for data mining - Survey and opportunities for big data. 4OR 17(2): 115-139 (2019)
• 
  Lucien Mousin, Marie-Eléonore Kessaci, Clarisse Dhaenens:
  Exploiting Promising Sub-Sequences of Jobs to solve the No-Wait Flowshop Scheduling Problem. CoRR abs/1903.09035 (2019)
• 2017
• 
  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)
• 
  Marie-Éléonore Kessaci-Marmion, Clarisse Dhaenens, Jérémie Humeau:
  Neutral Neighbors in Bi-objective Optimization: Distribution of the Most Promising for Permutation Problems. EMO 2017: 344-358
• 
  Lucien Mousin, Marie-Eléonore Kessaci, Clarisse Dhaenens:
  A New Constructive Heuristic for the No-Wait Flowshop Scheduling Problem. LION 2017: 196-209
• 2016
• 
  Marie-Eléonore Marmion, Hernán E. Aguirre, Clarisse Dhaenens, Laetitia Jourdan, Kiyoshi Tanaka:
  Multi-objective Neutral Neighbors': What could be the definition(s)? GECCO 2016: 349-356
• 
  Lucien Mousin, Laetitia Jourdan, Marie-Éléonore Kessaci-Marmion, Clarisse Dhaenens:
  Feature Selection Using Tabu Search with Learning Memory: Learning Tabu Search. LION 2016: 141-156
• 
  Maxence Vandromme, Julie Jacques, Julien Taillard, Laetitia Jourdan, Clarisse Dhaenens:
  A Scalable Biclustering Method for Heterogeneous Medical Data. MOD 2016: 70-81
• 2015
• 
  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)
• 
  Aymeric Blot, Hernán E. Aguirre, Clarisse Dhaenens, Laetitia Jourdan, Marie-Eléonore Marmion, Kiyoshi Tanaka:
  Neutral but a Winner! How Neutrality Helps Multiobjective Local Search Algorithms. EMO (1) 2015: 34-47
• 
  Benjamin Fisset, Clarisse Dhaenens, Laetitia Jourdan:
  MO-Mine_clust: A Framework for Multi-objective Clustering. LION 2015: 293-305
• 
  Julie Hamon, Julie Jacques, Laetitia Jourdan, Clarisse Dhaenens:
  Knowledge Discovery in Bioinformatics. Handbook of Computational Intelligence 2015: 1211-1223
• 
  Clarisse Dhaenens, Laetitia Jourdan, Marie-Eléonore Marmion:
  Learning and Intelligent Optimization - 9th International Conference, LION 9, Lille, France, January 12-15, 2015. Revised Selected Papers. Lecture Notes in Computer Science 8994, Springer 2015, ISBN 978-3-319-19083-9 [contents]
• 2013
• 
  Sébastien Vérel, Arnaud Liefooghe, Laetitia Jourdan, Clarisse Dhaenens:
  On the structure of multiobjective combinatorial search space: MNK-landscapes with correlated objectives. Eur. J. Oper. Res. 227(2): 331-342 (2013)
• 
  Marie-Eléonore Marmion, Laetitia Jourdan, Clarisse Dhaenens:
  Fitness Landscape Analysis and Metaheuristics Efficiency. J. Math. Model. Algorithms 12(1): 3-26 (2013)
• 
  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
• 
  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
• 
  Marie-Eléonore Marmion, Aymeric Blot, Laetitia Jourdan, Clarisse Dhaenens:
  Neutrality in the Graph Coloring Problem. LION 2013: 125-130

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