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Adán José García
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2020 – today
- 2024
- [j10]Adán José García
, Julie Jacques
Metaheuristic Biclustering Algorithms: From State-of-the-art to Future Opportunities. ACM Comput. Surv. 56(3): 69:1-69:38 (2024) - [c12]Adán José García, Julie Jacques, Clément Chauvet, Vincent Sobanski, Clarisse Dhaenens:
HBIC: A Biclustering Algorithm for Heterogeneous Datasets. ECAI 2024: 3088-3095 - [i2]Adán José García, Julie Jacques, Clément Chauvet, Vincent Sobanski, Clarisse Dhaenens:
HBIC: A Biclustering Algorithm for Heterogeneous Datasets. CoRR abs/2408.13217 (2024) - 2023
- [j9]Adán José García
C3-IoC: A Career Guidance System for Assessing Student Skills using Machine Learning and Network Visualisation. Int. J. Artif. Intell. Educ. 33(4): 1092-1119 (2023) - [j8]Adán José García
What's in a distance? Exploring the interplay between distance measures and internal cluster validity in multi-objective clustering. Nat. Comput. 22(2): 259-270 (2023) - [j7]Adán José García
CVIK: A Matlab-based cluster validity index toolbox for automatic data clustering. SoftwareX 22: 101359 (2023) - [j6]Mario Garza-Fabre
Evolutionary Multiobjective Clustering Over Multiple Conflicting Data Views. IEEE Trans. Evol. Comput. 27(4): 817-831 (2023) - 2022
- [c11]Adán José García
Multi-view Clustering of Heterogeneous Health Data: Application to Systemic Sclerosis. PPSN (2) 2022: 352-367 - [i1]Adán José García, Julie Jacques, Vincent Sobanski, Clarisse Dhaenens:
Biclustering Algorithms Based on Metaheuristics: A Review. CoRR abs/2203.16241 (2022) - 2021
- [j5]Adán José García
An evolutionary many-objective approach to multiview clustering using feature and relational data. Appl. Soft Comput. 108: 107425 (2021) - [j4]Dirk Siegmund, Biying Fu, Adán José García
Detection of Fiber Defects Using Keypoints and Deep Learning. Int. J. Pattern Recognit. Artif. Intell. 35(5): 2150016:1-2150016:22 (2021) - [j3]Absalom E. Ezugwu
Automatic clustering algorithms: a systematic review and bibliometric analysis of relevant literature. Neural Comput. Appl. 33(11): 6247-6306 (2021) - [c10]Adán José García
On the Interaction Between Distance Functions and Clustering Criteria in Multi-objective Clustering. EMO 2021: 504-515 - [c9]Adán José García
A survey of cluster validity indices for automatic data clustering using differential evolution. GECCO 2021: 314-322
2010 – 2019
- 2019
- [c8]Adán José García
Many-view clustering: an illustration using multiple dissimilarity measures. GECCO (Companion) 2019: 213-214 - 2017
- [c7]Adán José García
Evolutionary Clustering Using Multi-prototype Representation and Connectivity Criterion. MCPR 2017: 63-73 - 2016
- [j2]Adán José García
Automatic clustering using nature-inspired metaheuristics: A survey. Appl. Soft Comput. 41: 192-213 (2016) - 2015
- [j1]Adán José García
Rule-based approach for topic maps learning from relational databases. Expert Syst. J. Knowl. Eng. 32(5): 609-621 (2015) - 2012
- [c6]Adán José García
Building topic maps from relational databases. CCE 2012: 1-6 - 2011
- [c5]Adán José García
A Simulated Annealing Algorithm for the Problem of Minimal Addition Chains. EPIA 2011: 311-325 - [c4]Arturo Rodríguez-Cristerna, José Torres-Jiménez
A Mutation-Selection Algorithm for the Problem of Minimum Brauer Chains. MICAI (2) 2011: 107-118 - 2010
- [c3]Ramón Zataraín-Cabada, María Lucía Barrón-Estrada, Viridiana Ponce Angulo, Adán José García
A Framework for Creating, Training, and Testing Self-Organizing Maps for Recognizing Learning Styles. Edutainment 2010: 53-64 - [c2]Ramón Zataraín-Cabada, María Lucía Barrón-Estrada
Identification of Felder-Silverman Learning Styles with a Supervised Neural Network. ICIC (2) 2010: 479-486 - [c1]Ramón Zataraín-Cabada, María Lucía Barrón-Estrada, Viridiana Ponce Angulo, Adán José García
A Learning Social Network with Recognition of Learning Styles Using Neural Networks. MCPR 2010: 199-209
Coauthor Index
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last updated on 2024-10-28 21:16 CET by the dblp team
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