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Metaheuristics for Big Data

1, 2016

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Learning and Intelligent Optimization: 9th International Conference, LION 9, Lille, France, January 12-15, 2015. Revised Selected Papers

2015, 2015

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Metaheuristics for data mining: survey and opportunities for big data

Annals of Operations Research, 2022-07, Vol.314 (1), p.117-140

2022

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Metaheuristics for data mining: Survey and opportunities for big data

4OR, 2019-06, Vol.17 (2), p.115-139

2019

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γ-clustering problems: Classical and parametrized complexity

Theoretical computer science, 2024-11, Vol.1018, p.114784, Article 114784

2024

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A Biclustering Method for Heterogeneous and Temporal Medical Data

IEEE transactions on knowledge and data engineering, 2022-02, Vol.34 (2), p.506-518

2022

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Synergies between operations research and data mining: The emerging use of multi-objective approaches

European journal of operational research, 2012-09, Vol.221 (3), p.469-479

2012

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On the structure of multiobjective combinatorial search space: MNK-landscapes with correlated objectives

European journal of operational research, 2013-06, Vol.227 (2), p.331-342

2013

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Metaheuristics for data mining

4OR, 2019-06, Vol.17 (2), p.115-139

2019

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Metaheuristic Biclustering Algorithms: From State-of-the-art to Future Opportunities

ACM computing surveys, 2023-10, Vol.56 (3), p.1-38, Article 69

2023

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Minimizing the makespan on a batch machine with non-identical job sizes: an exact procedure

Computers & operations research, 2002-06, Vol.29 (7), p.807-819

2002

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Conception of a dominance-based multi-objective local search in the context of classification rule mining in large and imbalanced data sets

Applied soft computing, 2015-09, Vol.34, p.705-720

2015

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Solving a dial-a-ride problem with a hybrid evolutionary multi-objective approach: Application to demand responsive transport

Applied soft computing, 2012-04, Vol.12 (4), p.1247-1258

2012

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Improving the State of the Art in Inexact TSP Solving Using Per-Instance Algorithm Selection

Learning and Intelligent Optimization, 2015, Vol.8994, p.202-217

2015

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Biclustering similarity measures for heterogeneous data

AIP Conference Proceedings, 2018, Vol.2016 (1)

2018

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LS-PON: A Prediction-Based Local Search for Neural Architecture Search

Machine Learning, Optimization, and Data Science, 2023, Vol.13810, p.108-122

2023

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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

International journal of medical informatics (Shannon, Ireland), 2020-10, Vol.142, p.104242-104242, Article 104242

2020

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Metaheuristics for Machine Learning: New Advances and Tools

1, 2023

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Extraction and optimization of classification rules for temporal sequences: Application to hospital data

Knowledge-based systems, 2017-04, Vol.122, p.148-158

2017

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On the structure of multiobjective combinatorial search space: MNK-landscapes with correlated objectives

European journal of operational research, 2013-06, Vol.227 (2), p.31

2013

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K-PPM: A new exact method to solve multi-objective combinatorial optimization problems

European journal of operational research, 2010, Vol.200 (1), p.45-53

2010

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Solving a Dial-a-Ride Problem with a Hybrid Multi-objective Evolutionary Approach: Application to Demand Responsive Transport

Applied soft computing, 2012-04, Vol.12 (4), p.1247-1258

2012

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A Warped Kernel Improving Robustness in Bayesian Optimization Via Random Embeddings

Learning and Intelligent Optimization, 2015, Vol.8994, p.281-286

2015

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Complexity results for parallel machine problems with a single server

Journal of scheduling, 2002-11, Vol.5 (6), p.429-457

2002

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A Comparative Study on Self-Adaptive Differential Evolution Algorithms for Test Functions and a Real-World Problem

Learning and Intelligent Optimization, 2015, Vol.8994, p.131-136

2015

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Metaheuristics for Big Data

Learning and Intelligent Optimization: 9th International Conference, LION 9, Lille, France, January 12-15, 2015. Revised Selected Papers

Metaheuristics for data mining: survey and opportunities for big data

Metaheuristics for data mining: Survey and opportunities for big data

γ-clustering problems: Classical and parametrized complexity

A Biclustering Method for Heterogeneous and Temporal Medical Data

Synergies between operations research and data mining: The emerging use of multi-objective approaches

On the structure of multiobjective combinatorial search space: MNK-landscapes with correlated objectives

Metaheuristics for data mining

Metaheuristic Biclustering Algorithms: From State-of-the-art to Future Opportunities

Minimizing the makespan on a batch machine with non-identical job sizes: an exact procedure

Conception of a dominance-based multi-objective local search in the context of classification rule mining in large and imbalanced data sets

Solving a dial-a-ride problem with a hybrid evolutionary multi-objective approach: Application to demand responsive transport

Improving the State of the Art in Inexact TSP Solving Using Per-Instance Algorithm Selection

Biclustering similarity measures for heterogeneous data

LS-PON: A Prediction-Based Local Search for Neural Architecture Search

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

Metaheuristics for Machine Learning: New Advances and Tools

Extraction and optimization of classification rules for temporal sequences: Application to hospital data

On the structure of multiobjective combinatorial search space: MNK-landscapes with correlated objectives

K-PPM: A new exact method to solve multi-objective combinatorial optimization problems

Solving a Dial-a-Ride Problem with a Hybrid Multi-objective Evolutionary Approach: Application to Demand Responsive Transport

A Warped Kernel Improving Robustness in Bayesian Optimization Via Random Embeddings

Complexity results for parallel machine problems with a single server

A Comparative Study on Self-Adaptive Differential Evolution Algorithms for Test Functions and a Real-World Problem

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