Metric learning for monotonic classification: turning the space up to the limits of monotonicity.
Appl. Intell., March, 2024
Semi-supervised clustering with two types of background knowledge: Fusing pairwise constraints and monotonicity constraints.
Inf. Fusion, February, 2024
Multimodal pedestrian detection using metaheuristics with deep convolutional neural network in crowded scenes.
Inf. Fusion, July, 2023
Semi-Supervised Constrained Clustering: An In-Depth Overview, Ranked Taxonomy and Future Research Directions.
CoRR, 2023
3SHACC: Three stages hybrid agglomerative constrained clustering.
Neurocomputing, 2022
A Preliminary Approach for using Metric Learning in Monotonic Classification.
Proceedings of the Advances and Trends in Artificial Intelligence. Theory and Practices in Artificial Intelligence, 2022
Monotonic Constrained Clustering: A First Approach.
Proceedings of the Advances and Trends in Artificial Intelligence. Theory and Practices in Artificial Intelligence, 2022
Adapting K-Means Algorithm for Pair-Wise Constrained Clustering of Imbalanced Data Streams.
Proceedings of the Hybrid Artificial Intelligent Systems - 17th International Conference, 2022
ME-MEOA/DCC: Multiobjective constrained clustering through decomposition-based memetic elitism.
Swarm Evol. Comput., 2021
Decomposition-Fusion for Label Distribution Learning.
Inf. Fusion, 2021
Enhancing instance-level constrained clustering through differential evolution.
Appl. Soft Comput., 2021
DILS: Constrained clustering through dual iterative local search.
Comput. Oper. Res., 2020
Agglomerative Constrained Clustering Through Similarity and Distance Recalculation.
Proceedings of the Hybrid Artificial Intelligent Systems - 15th International Conference, 2020
Improving constrained clustering via decomposition-based multiobjective optimization with memetic elitism.
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020